We often talk about bringing the outdoors in, but the irony is that many of us often neglect spending quality time outside. In Oregon, certainly the most jaw-dropping state in the Union, we have no excuse to stay cooped up indoors. And even with nature's expansive domain, some of its most welcoming corners are in our very own backyards. It's time we make the most of them.
The Audubon Society Backyard Habitat Program covers over 200 acres of backyards in Portland and has distributed over 15,000 native plants this year.
An architect's stunning design blurs indoor and outdoor space but poses many challenges for the artful builder.


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Reeling at Altitude: Missives from the 2020 Sundance Film Festival, Part One
Jumbo | Courtesy of Sundance Institute
There's a question that has long been my personal riddle of the sphinx: what is "a Sundance movie"?
The term has an undeniable connotation, but (to paraphrase Justice Potter Stewart), I can't define it even though I know it when I see it. In a critics' roundtable published by The Hollywood Reporter following last year's festival, Jon Frosch described this "sometimes disparagingly employed term" as traditionally connoting "a certain kind of lily-white angst/quirk-athon a la Garden State, Little Miss Sunshine or Napoleon Dynamite," and that's about as close to a colloquial definition as I can imagine. Sundance remains by far the American film festival with the greatest name recognition, yet by the end of the millennium's first decade, that name could be used as a jeer just as often as an accolade.
Another decade or so removed from those particular "quirk-athons," though, what Sundance means has shifted—and, more than ever it seems, stratified. It can be easy to feel like there are two festivals running simultaneously—on the one hand, as Vanity Fair critic Richard Lawson recently mentioned on the podcast "Little Gold Men," the decreasing multiplex space afforded to non-franchise films means that the traditional seller's market aspect of Sundance has diminishing viability. Triumphing in a heated bidding war can more often than not mean acquiring a movie that won't find the necessary oxygen to compete (see: Dope, a sensational coming-of-age comedy that was among the biggest sales of the 2015 festival only to land outside the top 100 films at the year's box office). "Distributors," as Lawson points out, are adopting an "austerity mindset" while Sundance is becoming "a showcase for stuff that Netflix or A24 already has." When the festival's early days are dominated by discussion of a Taylor Swift documentary that will be available on that ubiquitous streaming service a week after its high-profile Eccles Center premiere, it can be easy to wonder what Sundance even represents in 2020.
Running alongside this trade show, however, is the slate of low-profile discoveries that push the boundaries of how a camera can influence hearts and minds in the 21st century. During a given time slot this year, Park City visitors can choose between that Taylor Swift profile, a Ukranian documentary that sees a family use art to make sense of life during wartime, the first feature ever directed by a Saudi woman, or a romance between Mexican men weighing their love against the risk of crossing the border into Trump's America. What Sundance means may have shifted and bifurcated, but it remains large and ever-expanding. While so many forces in the entertainment industry pay lip service to diversity efforts, Sundance has admirably put its money where its mouth is—according to a fact sheet provided to critics at the start of this year's festival, 42% of features on the 2020 slate were directed by women, 34% were directed by filmmakers of color, and 14% were directed by filmmakers identifying as LGBTQ+. There is undeniable and pressing work to be done in raising those numbers, but with its status as best-in-class for inclusion among the top global festivals, Sundance's contradictions contain multitudes.
We'll shortly transition to six case studies of what a "Sundance movie" might look like at the dawn of the '20s, but first, a brief disclaimer: though Bright Wall/Dark Room is typically the Wild West when it comes to so-called spoilers, I recognize that few people reading this piece will have the opportunity to see these films anytime soon, and so I will take pains to avoid mentioning specific plot details beyond basic setups. However, I will be discussing the full shape of each film, including offering non-specific perspectives on their conclusions. I write with respect to that contingent that prefers to enter a film with as little foreknowledge as possible, but I'd also gently ask that group to consider why they've opened this tab in the first place, and whether they might be happier closing it.
With that settled, I'll return to the words of Jon Frosch, who determined that the Sundance ideal remains the hunt for "that adrenaline-shot of discovery." And, for all the tumult and uncertainty in the landscape of Hollywood and beyond, I'm happy to report that I experienced this thrill more often than not in the first three days of my Sundance sojourn, and it was never more potent than in my opening night selection.
Summertime (Carlos Lopez Estrada) | Courtesy of Sundance Institute
Summertime is the type of unclassifiable movie that makes you want to reach for comparisons. The easiest might be "a Gen-Z Slacker," as it sketches intersecting vignettes of disparate young people drifting through one Los Angeles day. But no comparison—even, as I heard one audience member vividly suggest as the credits rolled, "In the Heights meets Tangerine"—can quite approximate the effect of this magic realist spoken word musical that posits self-expression as the ultimate form of healing.
Director Carlos López Estrada follows his urgent but scattered 2018 debut Blindspotting by collaborating with 25 young Angeleno poets, each of them listed as co-screenwriter (Estrada takes only an "additional story" credit). It may seem counterintuitive to argue that this deliberately formless work is more cohesive than the conventionally plotted Blindspotting, but Estrada displays a remarkable ability to identify his strengths and then sprint towards them even at the possible expense of commercial viability (a cynical presumption on which I dearly hope to be proven wrong).
Shedding the classic storytelling structure of Blindspotting, Estrada takes its most confounding element—the shocking and surreal climactic burst of poetic passion—and fashions an entire film to support this type of electrifying moment that was unfortunately doomed to sit uneasily alongside traditional storytelling. Where some directors might sand off the controversial aspects of their early work in the interest of carving out a sustainable career, Estrada does the opposite, conjuring a world where explosions of ecstatic poetry are commonplace, where a bigot on a bus can be defeated through the power of rhythmic rhyme—a world where, as one character titles her self-help book, you can "Rap Battle Your Demons."
In the wake of the premiere, the most common complaint seems to be the unapologetically amateur nature of the poetry, which represents at least half the script. The point is undeniable, but it's also, at least to my eyes, what makes the film remarkable. The young protagonists of Summertime are struggling to make sense of their identities and their place in the world, and their skills with self-expression are appropriately half-baked. If Estrada's film can often feel like the world's glossiest class project—according to press notes, the script is adapted from a real high school showcase—that means it represents an unusually raw vision of the world as seen by its emerging voices. Estrada, evincing an admirable lack of ego, provides just enough supporting style and structure to create a crowd-pleasing work of art while remaining unobtrusive enough to allow his young collaborators the status of primary auteurs.
While there are frequent jabs at typical Gen-Z idiosyncrasies (notably one perfectly imperfect use of "praxis"), the satire carries a sense of good-humored self-reflection as these characters take stock of their identities on the cusp of adulthood. While Slacker is the easy comparison, I found myself thinking more often of Dazed and Confused, another story set at the fault line of the painfully familiar and the thrilling unknown. Though the world of Summertime may seem supernaturally supportive of its characters (nowhere more evidently than in the most overtly surreal, and most outright comic, element, which sees one pair of characters experience years' worth of incident in just a few hours), it never elides the spiritual wounds inflicted on its young heroes by indifferent or hostile powers. It simply acknowledges and honors that pain, and then returns to its steadfast belief that the arc of history is bending in their direction.
In an introductory video attached to the Summertime profile on the Sundance website, Estrada cedes his time to the 25 young screenwriters, each of whom offers some personal introduction ("I'm a Pisces moon;" "I'm a stressed-out college student") but one in particular rang in my head throughout the film, only gaining in resonance as the climax approached: "I'm Gordon Ip," says the young man who commands the final stretch of Summertime with a showstopping act of service industry rebellion, "and I think you deserve love and affection."
If Summertime risks dipping its toe into the saccharine, it's all in the service of that essential message: everyone (with the possible exception of bus-riding bigots) is deserving of love and affection, and I can hardly think of a more worthy theme, or a more uniquely remarkable film.
"Uniquely remarkable" is an apt descriptor for several of the films I watched in this first half of my trip to Park City, but the significance of the term can diverge sharply—and not always for the best.
Jumbo is destined to be remembered for a pithy logline—it's the one where a woman has an affair with an amusement park ride—and that simplistic description is by no means inapt. This is, indeed, a movie about a sexual affair between a human and an object. But what appears at first to be a psychologically acute story of objectophilia (a real condition marked by sexual and romantic attraction to inanimate objects, one that studies suggest is frequently correlated with autism spectrum disorders) transforms into something far eerier before taking an abrupt and deflating turn into facile uplift. It's an odd medley, but what do you expect from the one where a woman has an affair with an amusement park ride?
Jumbo flirts with easy clichés—don't let the subtitles fool you, this has all the DNA of a mid-2000s "Sundance movie," right down to the triumphant hair-metal needle drop accompanying the soaring climax—but it's largely saved by the seriousness with which it takes the interior struggles of protagonist Jeanne (Portrait of a Lady on Fire star Noémie Merlant, cementing her starmaking run with a performance diametrically opposed but no less magnetic). Jeanne is neurodivergent, but her ostensibly bizarre longings are treated with the same dignity regularly afforded neurotypical characters struggling towards self-actualization (the story acknowledges that Jeanne has been diagnosed with some psychological condition, one that has taken a significant toll on her family, though it elides naming that condition in favor of a disappointing deployment of "special," absolving any necessity to faithfully represent clinical symptoms). At no point is she presented as worthy of mockery, and while I heard scattered laughs during one particularly stark sexual encounter between Jeanne and Jumbo (the tilt-a-whirl-esque attraction recently installed in the suburban park where she works maintenance) the laughter felt more astonished than derisive—the sole outright villains in this otherwise generous story are those who would dare to sneer at Jeanne.
I have overheard complaints around town that the mechanical focus of Jeanne's objectophilia serves no thematic function—she could just as easily have been in love with a plant, one industry member groused in a line later that day—but I would point to the overwhelming euphoria as Jumbo takes Jeanne into his whirling arms (yes, the film does definitively gender the ride) and removes her tiresome connection to gravity. Jeanne speaks of her longing to be taken outside of herself, and writer/director Zoé Wittock has fashioned an ideal device to externalize that desire—not to mention allowing for several ethereal neon reveries that couldn't help but take my breath away.
It's notable, however, that everything I appreciate in the film comes in the first two acts. The story's deliberate provocations reach their apex in a hallucinatory interlude calling to mind Under the Skin, yet in what feels almost like a twist ending, the uncanny is abruptly subsumed by the sweet, and the third act is devoted to the trite lesson that our differences make us special. The final moments of Jumbo call to mind nothing more than Little Miss Sunshine, and it's strange to feel simultaneously elated and deflated, as the simplistic ending comes at the expense of the raw psychological pain that defined the preceding hour.
If my greatest complaint is that the movie is too crowd-pleasing, then it must be an easy one to recommend, though I do wonder what the intersection could be of audiences looking for both abstract science fiction (the film plays coy as to whether Jumbo is indeed sentient rather than simply Jeanne's delusion, but seems to suggest the former) and life-affirming sweetness. They're two great tastes that, unfortunately, seldom taste great together.
That sense of unnerving tonal whiplash would return to me later that day, though this time the effect was far more potent, and even outright thrilling.
Black Bear (Lawrence Michael Levine) | Courtesy of Sundance Institute
There is no subgenre of independent film more tiresome than the "lake house movie." When a story features a small group of disaffected, affluent young white people holing up at a remote cabin to hash out their petty squabbles, the results tend to reek of a director more concerned with cheap convenience than compelling storytelling.
The first act of Black Bear (which is divided into two theatrical acts rather than the conventional cinematic three) follows this formula to the letter, as Aubrey Plaza's enigmatic filmmaker visits a lakeside retreat in search of inspiration only to be drawn into the domestic agonies of a couple (Chrisopher Abbott and Sarah Gadon) who are trying not particularly hard to pretend they don't hate one another. After nearly an hour of a sexually charged millennial riff on Who's Afraid of Virginia Woolf? I found myself struggling to stay engaged, even as the story's quick descent into self-conscious hysteria indicated something trickier might be at play.
It would be criminal to reveal what happens in the second half of Black Bear, which is convenient as a critic because describing it would also be incredibly difficult. Suffice it to say writer/director Lawrence Michael Levine takes the trite "lake house movie" and turns it inside out, forcing the viewer to reconsider everything that came before while sprinting to keep up with what's unfolding now, not to mention trying—quite likely in vain—to find the coherent plot thread that might unite the two. This shocking gambit results in an hour of electrifying, effervescent, and devastating filmmaking, even if it ultimately leaves the viewer holding a mass of seemingly contradictory puzzle pieces with little guiding sense of how to put them together.
Black Bear is the type of film built for fan theorizing—there are ample clues as to what's "really happening," but the film is so deliberately abstract that it would seem the height of folly to suggest textual evidence supports a clear interpretation. Immediately upon finishing, I began trying to diagram my own grand unified theory only to quickly realize I was far more interested in reflecting on the thrilling and emotional head trip I'd witnessed, "solving it" be damned.
More than any film I've seen in the past few years, Black Bear benefits from extratextual awareness. The first closing credit is a hand-written dedication to "Sophia," and those familiar with Levine's work will recognize the nod to his wife and frequent collaborator, Sophia Takal. The dedication turns subtext into text within this nesting-doll story of the ways partners can manipulate and abuse one another when life intermingles with work, and the psychological ravages that can result. The film practically begs the viewer to consider Levine as an invisible and omnipotent co-lead, and though I have to wonder how effective the experience might be for anyone unfamiliar with his collaborations with Takal, not to mention the wisdom of crafting the first half of a film to be intentionally stilted, for anyone willing to continue pondering the experience beyond the end credits, it's an unusually rich one.
Perhaps most rewarding of all, Black Bear is a massive leap in scope and ambition for Levine, whose previous work has often riffed—albeit unusually effectively—on existing tropes. Wild Canaries—in which he co-stars with Takal as another pair of lovers trying to pretend they don't hate each other—is a Brooklyn-set comic noir that features scattered moments of bracing emotion but nevertheless evaporates as soon as the credits roll. Levine followed that project with the screenplay for Takal's directorial project, Always Shine, an engaging but nevertheless slight riff on the "persona swap" tradition, and that experimental dip into Bergmanesque waters serves as a link to Black Bear. Levine now moves beyond thematic sampling into the more metatextual and cerebral experimentations of Bergman and his midcentury European contemporaries, but if there is a case to be made that Levine is once again putting a 21st century spin on existing tradition, there's an even stronger case to be made that he's now made the shift into full-throated originality, and for all the puzzling chaos still ringing in my mind, I'm eager to see where he takes his craft next.
If Levine has used Sundance 2020 to stake his claim as a fully-formed auteur, he's joined by another director who attempted an even tougher trick in what's almost certainly the buzziest film of the festival, and among the most divisive.
Zola (Janicza Bravo) | Courtesy of Sundance Institute
With an hour to go before the doors opened, the line for the press and industry screening of Zola had packed the holding tent and extended down the corridor, and the queue continued to grow even as it became clear the demand for seats would far exceed the supply. That desperate persistence is easy to understand—few films in recent memory have come loaded with as much intrigue and mystery (carefully cultivated by A24, who released only one promotional still and withheld press notes until the moment that screening ended).
Even among a lineup dense with alluring loglines, Zola stands out as the first feature film ever adapted from a Twitter thread. That announcement had certainly piqued my interest—like so many of the Extremely Online, I remembered the week in 2015 that social media was set ablaze by the epic thread, soon referred to simply as #TheStory, that began, "Y'all wanna hear a story about why me & this bitch here fell out??????? It's kind of long but full of suspense"—but my curiosity went into overdrive with the announcement that the director would be Janicza Bravo. I'd been fascinated by Bravo's short films, as well as her debut feature, Lemon (a vehicle for her husband, abrasive comedian Brett Gelman), which tend to function as collisions between Adult Swim and Samuel Beckett. With a history of such aggressively hysterical and alienating work, it was clear that Bravo's interpretation of Zola would be no mere recounting of events.
For anyone who may not recall #TheStory, the story is this: Zola (newcomer and instant star Taylour Paige) is a Detroit waitress and stripper who experiences an idyllic evening of friendship at first sight with fellow stripper Stefani (Riley Keough). The following day, Stefani impulsively invites Zola to accompany her for a weekend of stripping in Florida, and Zola—despite the misgivings of her concerned but supportive boyfriend—joins Stefani and her two male companions for what's meant to be a carefree and lucrative road trip. Instead, as the trip's focus turns from stripping to more intimate sex work…well, Zola and Stefani fall out, and if—at a hyperkinetic 90 minutes—it's not particularly long, it's unquestionably full of suspense.
Early reactions posit Zola as a melding of Spring Breakers and The Florida Project, and I have to admit, I find the comparisons baffling. Despite their kinship as portraits of Floridian hedonism, Zola has none of the former's droning hypnosis, nor any of the latter's naturalistic grace. Comparing Zola to any prior work, in fact, strikes me as entirely misguided. Bravo (along with her co-writer, celebrated playwright Jeremy O. Harris) sets out to develop an entirely new cinematic language, and she succeeds wildly—until, abruptly and heartbreakingly, she doesn't.
The fact that this is the first movie ever based on a Twitter thread is no mere trivia item. Bravo has been tasked with interpreting an entirely new form of storytelling, one that doesn't obey any of the rules that have been tried and tested for centuries. Reading #TheStory is a chaotic experience; plot beats necessarily come in brief bursts designed to keep the reader pushing that digital lever for bites of intrigue, and Bravo envisions remarkably innovative techniques to mimic the dopamine rush of following a story that's fighting to keep you glued to your phone. Most notable is the sound design, which makes use of familiar chimes and chirps to suggest either that Zola is composing #TheStory in her head as we follow her chaotic odyssey, or else to acknowledge that we're viewing the events as related through the language of social media.
This technique could easily be labeled a gimmick, but it weaves into a broader tapestry of formal contradictions—moments of freeway pastoralism evoke the outsider's lens of Andrea Arnold's American Honey, while periodic visits to an eerie internal dreamscape recall cinematographer Ari Wegner's recent work on In Fabric; abrupt whiplashes between outright comedy (Nicholas Braun as Stefani's unstably jealous boyfriend feels like nothing less than an alternate-universe Cousin Greg) and ferocity (Colman Domingo's sex trafficker keeps charisma and menace in such precise balance that it's impossible to keep your eyes off him) are perversely unified by the gentle chimes of Mica Levi's score.
The patchwork of mood and tone serves the aforementioned role in approximating the disunified experience of social media storytelling, but perhaps more significantly it functions as a potent destabilizing force in a story that could easily lapse into familiar exploitative tropes. Bravo and Harris are tasked with exploring an urgent epidemic of abuse, one often depicted with a raw brutality that can quickly slide into voyeuristic detachment. But Zola is no victim, and even Stefani, subjected to frequent manipulation and abuse, is granted a level of dignity and agency that similar stories often struggle to muster. By playing fast and loose with tone and style, Bravo kicks away crutches that viewers (by which I do generally mean white ones) may be accustomed to leaning on as they process such a story, inviting—if not forcing—reconsideration of the biases that influence expectations for a story of sex work.
I mentioned that Zola works until it doesn't, and the final dip into dissatisfaction is shockingly precipitous. Without going into detail, Bravo and Harris change one key beat in #TheStory's denouement, and though it may have been a necessary shift to save the final moments from cartoonishness, it throws off the chemistry in the final stretch. The shrug of an ending is particularly puzzling given that the film's twin inspirations (#TheStory and David Kushner's Rolling Stone piece that explores the participants' Rashomon-style conflicting recollections, which Zola nods to in one abrupt and bafflingly outrageous interlude) provide multiple options for catharsis. In all likelihood Bravo and Harris have a thoughtful and resonant defense of their choice, but it's hard not to feel like the camera simply ran out, leaving no choice but to roll the credits.
But this disappointment has to be weighed against the fact that Janicza Bravo approached a high-wire job—make an antic comedy that takes sex trafficking seriously—with a ferocious and singular eye. There was a window, shortly after the initial tweetstorm, when James Franco was set to write and direct the authorized adaptation of #TheStory, and that possibility serves as a horrific what-if—we know exactly what that familiar and ugly version of Zola would have looked like, and we must count ourselves blessed that Zola's story can instead serve as a platform to elevate Janicza Bravo as a major, fearless auteur.
To this point, I've been able to identify that "adrenaline-shot of discovery" to at least some extent in each of my initial Sundance picks. But now, sadly, it's my duty to report on the first outright disappointment of my week at altitude.
High Tide (Verónica Chen) | Courtesy of Sundance Institute
High Tide, the Argentinian psychodrama written and directed by Verónica Chen, seems designed to ask tough questions. Unfortunately, those questions feel too scattered to do much provoking, and the potential answers are disconcerting in ways it's hard to imagine were intentional.
The story opens abruptly, with protagonist Laura (Gloria Carrá) accepting the sexual overtures of Weisman (Jorge Sesán), the contractor whose crew is building a barbecue shed at her seaside home. Laura—as we learn through effectively detached drips of context—is married, and when Weisman disappears the following morning, his two workers (Cristian Salguero and Hector Bordoni) use her transgression as the opportunity for a campaign of menace, incrementally invading her home and sending her into a spiral of psychological collapse that quickly falls into a familiar playbook of woman-on-the-verge stories.
While this setup could make for enjoyable tension, the painful thorn at the base of High Tide lies in the fact that Laura and Weisman are of European descent, and the workers of indigenous descent. I can't claim any awareness of Argentinian cultural history, but from an American perspective, the optics of the battle between a helpless white woman and a pair of non-white psychological sadists are cringingly uncomfortable. It's certainly arguable that the story functions as social commentary, with Laura as either tacit villain or object of satire (comparisons to Parasite do seem inevitable) but by anchoring the viewer in her perspective, Weisman's crew are left seeming less like characters than borderline-supernatural agents of chaos, playing into ugly racial dynamics while offering no particular subversion. Laura may be cast as increasingly unsympathetic—as her stress peaks, she ineffectually begs the workers to respect their lower social standing—but alongside her vivid journey, her tormentors remain othered and narratively disenfranchised.
Paradoxically, this singular focus on Laura's experience is the film's greatest strength. The viewer is left with virtually no awareness of Laura's life outside the immediate events of the story, creating an effective claustrophobia that mirrors her own mental alienation. Chen has an admirable eye for her story's environment, creating chilling dread through simple composition of insert shots that explore the natural world. But Laura's journey to self-actualization—which manifests in a seemingly triumphant mockery of her nemesis' accent—leaves the story muddled, any moral ambiguity less provocative than unpleasant. On a purely semiotic level, brutal non-white men abusing a frightened white woman is imagery to be handled with extreme care, and it's painful to sit through a feature-length example of such tired dynamics only to be left with no particular insight.
But, as the song goes, if you want the rainbow, you must have the rain, and with that cloud passed, we can close out with one of the festival's triumphs, a radical act of genre revision and a bold step forward for another of America's most exciting emerging filmmakers.
Contrary to what you may have heard, Josephine Decker's Shirley is not a biopic. Adapted from a 2014 novel, Decker's fourth feature imagines the writing process of Jackson's 1964 novel Hangsaman through the eyes of Rose (a fictionalized character played by Odessa Young), who accompanies her husband (Logan Lerman) to Bennington, VT where the young couple fall under the sway of their hosts, unstable literary genius Jackson (Elisabeth Moss, continuing to fearlessly plumb new depths in depicting minds in turmoil) and her own insidiously affable professor husband (Michael Stuhlbarg).
I confess to leaving Shirley—Decker's first time directing someone else's script—feeling unsure what I want out of a Josephine Decker project. Each of her three features to date (wildly divisive Sundance breakout Madeline's Madeline, arthouse-grindhouse mashup Thou Wast Mild and Lovely, and fluid Arcadian nightmare Butter on the Latch) boasts electrifying craft but lacks the discipline to yield an emotionally resonant story. Thus I entered Shirley excited but wary. My wish would ostensibly be granted, a chance to see Decker's style applied to a more conventional story, but there was always that chance I might realize I hadn't been careful what I wished for.
I was thrilled to find Decker's style on full display from the first frames. Present are the woozy observational camerawork and gauzy claustrophobic close-ups of Madeline's Madeline, as well as frequent abstract horrors that call to mind the most unnerving moments of Butter on the Latch. Yet in seeing Decker elevate Sarah Gubbins' screenplay, I couldn't help feeling a mild loss, a sense that a joyfully rowdy voice—one that may be sporadically successful but always singularly daring—has been suppressed in service of someone else's story. For every thrilling burst of surrealism there's a beat of conventional plot that left me wistful for the palpable danger in every naturalistic moment of Madeline's Madeline. It's more than understandable that Decker's future career might depend on an ability to synthesize her style with more palatable subject matter, and Shirley is undeniably her film, bearing no sign of formal compromise. It's also, however, one that could have been directed—if to unquestionably lesser effect—by someone else, where Madeline's Madeline, despite any of my misgivings over her choices, could be the product of no mind but hers.
But enough of what this movie is not—I am coming dangerously close to inadvertently denigrating a truly great film. Shirley is a remarkable work destined to shake up any arthouse audience lucky enough to encounter it. More than any prior adaptation of Jackson's oeuvre, Decker and Gubbins conjure the vague normative menace that defines her classic works of subtle paranoia. As Shirley and Rose become increasingly bound to one another, and increasingly sequestered both physically and emotionally, Jackson's life bleeds into an evocation of the fearful isolationism of We Have Always Lived in the Castle, and as Shirley and Rose's respective husbands recede into their own world of blissful self-indulgence, Decker paints a bracing Gothic vision of a society that would rather see women made invalids than allowed to exercise true agency. There's a barely-suppressed rage coursing within Shirley as the two central women become ever more entwined, drawing from one another a power that may not save either from the social abuses they were born into but might at least generate enough energy to rebel.
There may be some growing pains in both pacing and lucidity as Decker transitions from exploring the far reaches of the avant garde to pushing the boundaries of the traditional, but it seems a small price to pay. In the hands of a less adventurous director, Shirley could have easily come across as standard historical fiction, but with Decker at the helm, it's elevated to something that gets under your skin in ways few similar films have ever dared.
The sun dances outside Park City's Eccles Center | photo by the author
Though Sundance may be synonymous with his name—not to mention sharing the name of perhaps his most iconic character—Robert Redford has eased back his public presence at an event that may well prove his greatest legacy. This year, he forewent the typical opening press conference, instead providing a brief and simple letter of welcome that was emailed to critics alongside that statistical breakdown of the festival's inclusion efforts. He did appear in person at the beginning of last year's festival, but his remarks were brief. "I don't think the festival needs a lot of introduction now," he concluded.
I would have to disagree. When there has never been a slimmer chance of mainstream viability for any film not based on a known quantity, the festival, and its role in the entertainment ecosystem, would seem to merit more discussion than ever. Even the programmed selections that might usually be labeled "Oscar bait" must be assessed in a world where a DC Comics property can lead the year's nominations. We may have some longstanding theoretical sense of what Sundance means, but its mission now has an urgency tinged with déjà vu. Redford founded the Sundance Institute in 1979 in hopes of keeping the idiosyncratic spirit of the New Hollywood alive amidst the rising uniformity of popular entertainment. He believed, as Peter Biskind writes in Down and Dirty Pictures, "that American film culture could contribute more than stale sequels and retreads, that historically, before the renewed hegemony of the studios, film had been a medium for genuine artists and could be again."
The history of the Sundance Film Festival has been dramatic, marked by triumph and ignominy, yet just over 40 years since Robert Redford's first summit in the Wasatch Mountains, we seem to have landed exactly where we started. Sundance is, once more, among the sole significant life support systems for films that dare to exist as distinct from that most distressingly cold artistic term, IP. And so we return to my personal riddle of the sphinx: what is "a Sundance movie" in a landscape that's come so far only to realize it was moving in a circle?
I write these words from the halfway point of my visit to Utah, and so the question remains up in the (thin) air. Come back for Part Two of these missives next week to see what answers the next batch of films might hold.
Black BearHigh TideJumbopostsShirleySummertimeSundanceSundance 2020Zola
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redpajama_set_name: RedPajamaCommonCrawl


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Civil rights hero and Democrat John Conyers has been felled by #MeToo
John Conyers—the Democratic party's longest-serving House representative—is stepping down from his House Judiciary Committee position amid allegations of sexual harassment.
The move comes just a handful of days after BuzzFeed reported the account of a former staffer who said she was fired by the congressman for resisting his sexual advances, then paid a settlement "more than $27,000" for a confidentiality agreement.
Conyers confirmed the settlement, but denied the harassment accusation, likening it to a "reasonable severance payment."
I deny these allegations, many of which were raised by documents reportedly paid for by a partisan alt-right blogger. I very much look forward to vindicating myself and my family before the House Committee on Ethics.
— John Conyers, Jr. (@RepJohnConyers) November 26, 2017
I cannot in good conscience allow these charges to undermine my colleagues in the Democratic Caucus, and my friends on both sides of the aisle in the Judiciary Committee and the House of Representatives.
Conyers' self-dismissal from the panel has notably caused a stir within an embattled Democratic party, with House Democratic leader Nancy Pelosi calling for "due process" on NBC's "Meet the Press" and questioning Conyers' accuser for not publicly coming forward.
This makes Conyers just the latest politician to fall to the #MeToo movement, which has seen the likes of Donald Trump, Bill Cosby, the late Roger Ailes, Bill O'Reilly, Harvey Weinstein, Louis C.K., Minnesota senator Al Franken, and Republican senate candidate Roy Moore all come under scrutiny for sexual abuse and harassment claims.
The allegations against Roy Moore have contributed to an escalating political standoff, with Moore still refusing to abandon his candidacy for the Alabama senate seat vacated by US Attorney General, Jeff Sessions. Donald Trump—accused of sexual misconduct by 17 women to date—has publicly given his complete support of Moore.
Meanwhile, John Conyers stands out as one of the most senior actively serving Democrats in the US Congress who's been accused of sexual harassment.
As the Washington Post reported earlier this month, Congress has paid out more than $17 million in employee-related settlements since 1997. The settlement issued by Conyers wasn't in that pool, with the payment instead coming from his own office's budget.
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When you can, try to collide with another player. Being able to predict where they are going ahead of time, will keep you from making contact. This will help you retain possession and will also prevent injury.
Practice whenever you get an opportunity. Make it a habit to bring along your soccer ball and whenever the moment strikes, take it out and practice those drills. You can also just direct the ball along with your feet whenever you walk from one place to another.
Try playing with people who are better than you are.
will be a lot more challenging if you practice with players who have more experience than you. Ask them for tips and pay attention to the strategies and moves they use. Try copying what they do and you will eventually become a better player.
Play with someone more experienced than you. It is one of the best ways to learn how to be better. By watching their style, you can mimic aspects of it in your own game. You may not even realize what you are doing in some cases, as you can pick things up without even trying in many cases.
When you are playing soccer, it is important for you to make split decisions and play the ball very quickly. If you take to long to think about each and every one of your plays, this will allow the opposing team to swoop in and take control of the ball.
Many times the ball will not be on the ground when it is time to shoot. By learning how to shoot using different techniques, you can be ready to make the shot even if the ball is in mid-air. This volleying technique should be learned by each soccer player for a successful season.
For a team to succeed in soccer there must be excellent communication between its players. This is essential to have in the soccer game. When you find an open spot, communicate it to the man with the ball. Learn the soccer terms that tell your teammate what you will do. If you intend to move between two defenders, "through" is the proper term.
Try not to stare at the ball. When you are playing soccer, you have to look up at all times. This is the only way you will be able to pass or shoot. This may seem very awkward, but you will get used to this as you keep playing the game.
One of the most important techniques to learn when playing soccer is learning to focus on the task at hand. Many talented soccer players fail because of their lack of focus. Even people with great technique can lose focus which in turn can result in their ability to play the game diminishing.


Oh, my, she is precious. I have been following your blog----you were due when our daughter-in-law was due. Our baby (fourth granddaughter--we have one grandson) was born last Friday morning at 6:15. She weighed 8 lbs. 5 oz.---19 1/2 inches long. Of course, we think she's beautiful but we're especially thankful that she's here and healthy. So thankful for your and your family's latest blessing as well.
such a cutie! that one with her looking at the camera is my fav and I think i need it for my frame!
she is such a beauty! just like her mommy!
I won't be online much till probably mid-Feb. I'm at a cafe and online for a few minutes. I knew I was going to miss her birth because of our move, and when I logged in and hopped over here, I saw Lola...and was almost crying!
so so cute and sweet!!!
She is so precious! Now you'll have to add her title - Princess - to your blog header! Congrats!
Yep. Definitely love her. She looks like Cameron!
Oh my Devin, she is beautiful. Can I just ask...what kind of socks did you find that actually stay on her tiny feet? I can't put my Lilly in anything but footed pjs because in all of the socks we own (and it's A.L.O.T.), I can't find a stinkin' pair that won't fall off!
what a precious little lamb! Praise the Lord!
Devin, SHE IS BEAUTIFUL!!! Congrats! And what a gorgeous name!
I wonder if that lesson really sunk in?


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text:
\subsection{Non-local Neighbor Extension}
Under the uniform message passing framework for homophilic graphs, the neighborhood is usually defined as the set of all neighbors one-hop away (\emph{e.g.}, GCN), which means only messages from proximal nodes in a graph are aggregated. However, such a local neighborhood definition might not be appropriate for heterophilic graphs, where nodes of the same class exhibit high structural similarity but can be farther away from each other. In light of these, current heterophilic GNNs attempt to extend the local neighbors to non-local ones primarily through two schemes: high-order neighbor mixing and potential neighbor discovery. As a result, the representation ability of heterophilic GNNs can be improved significantly by capturing the important features from distant but informative nodes. More details of these two schemes can be found as follows.

\subsubsection{High-order Neighbor Mixing}
Higher-order neighbor mixing allows the ego node to receive latent representations from their local one-hop neighbors and from further $k$-hop neighbors, so that the heterophilic GNNs can mix latent information from neighbors at various distances. Formally, the $k$-hop neighbor set is defined as $\mathcal{N}_k(v) = \{u: d(v, u)=k\}$, where $d(u,v)$ measures the shortest distance between nodes $u$ and $v$.

MixHop \cite{abu2019mixhop} is a representative method that aggregates messages from multi-hop neighbors. Apart from one-hop neighbors, MixHop also considers two-hop neighbors for message propagation. After that, the messages acquired from different hops are encoded by different linear transformations and then mixed by concatenation. Similar to MixHop, H2GCN \cite{h2gcn_zhu2020beyond} also proposes to aggregate information from higher-order neighbors at each message passing step. To provide a theoretical support, H2GCN verifies that two-hop neighbors tend to involve more nodes with the same class to the ego node, when the labels of one-hop neighbors are conditionally independent to the label of the ego node. Following a similar idea, UGCN \cite{jin2021universal} utilizes the two-hop network as one of propagation graphs to perform message passing. To control the scale of the two-hop neighbor set, UGCN further restricts the two-hop neighbor set in which nodes have at least two different paths to the connected ego nodes.
Besides, TDGNN \cite{wang2021tree} leverages the tree decomposition to separate neighbors at different $k$-hops into multiple subgraphs, and then propagates information on these subgraphs in parallel.
\subsubsection{Potential Neighbor Discovery}
Compared to high-order neighbor mixing methods directly utilizing the inherent structural information from graphs, potential neighbor discovery methods reconsider the definition of neighbors in heterophilic graphs and build innovative structural neighbors through the entire topology exploration with heterophily. Apart from the original neighbor set, these methods construct a new potential neighbor set $\mathcal{N}_p(v) = \{u: s(v,u) < \tau \}$, where $s(u,v)$ is a metric function that measures the distance between nodes $u$ and $v$ in a specifically defined latent space and $\tau$ is a threshold to limit the number of neighbors.

Typically, Geom-GCN~\cite{geom_pei2020geom} maps the input graph to a continuous latent space and defines the geometric relationships, \emph{i.e.}, split 2D Euclidean geometry locations, as the criteria to discover potential neighbors. Apart from inherent neighbors in original input graphs, neighbors that conform to the defined geometric relationships also participate in the message aggregation of GCN.
Furthermore, NLGNN~\cite{Liu2021NLGNN} and GPNN~\cite{yang2021graph} adopt the attention mechanism or leverage a pointer network to rank the potential neighbor nodes according to the attention scores or the relevant relationships to the ego node.
In this way, potential neighbors that are most similar to the ego node in heterophilic graphs can be discovered and selected. HOG-GCN~\cite{wang2021powerful} constructs a homophily degree matrix with the label propagation technique to explore the extent to which a pair of nodes belong to the same class in the entire heterophilic graph. By involving the class-aware information during the propagation process, intra-class nodes with higher heterophily (\emph{i.e.}, lower homophily degree) would contribute more to the neighbor aggregation than underlying inter-class nodes.
Also with the consideration of node similarity, UGCN~\cite{jin2021universal} and SimP-GCN \cite{simp_jin2021node} choose top $k$ similar node pairs in terms of feature-level cosine similarity for each ego node to construct the neighbor set through kNN algorithm. In contrast, WRGNN~\cite{SureshBNLM21} takes the degree sequence of neighbor nodes as the metric of structural similarity between ego nodes to reconstruct a graph in which different neighbors are indicated by different relations of edges. Moreover, BM-GCN~\cite{bm_gcn_he2021block} builds a new network topology based on a block similarity matrix, so that it can explore block-guided neighbors and conduct classified aggregation with different aggregation rules for homophilic and heterophilic nodes.
\input{03_table}
\subsection{GNN Architecture Refinement}
General GNN architectures in Eq.~(\ref{eq:GNN}) contain two essential components: the aggregation function $\operatorname{AGGREGATE}(\cdot)$ to integrate information from the discovered neighbors, and the update function $\operatorname{UPDATE}(\cdot)$ to combine the learned neighbor messages with the initial ego representation. Given the original local neighbors and the extended non-local neighbors on heterophilic graphs, existing GNN architecture refinement methods contribute to fully exploiting the neighbor information from the following aspects by accordingly revising $\operatorname{AGGREGATE}(\cdot)$ and $\operatorname{UPDATE}(\cdot)$: (1) {\it{Adaptive message aggregation}} discriminates the messages of similar neighbors from dissimilar ones; (2) {\it{Ego-neighbor separation}} focuses on the difference between ego representations and their neighbor messages; (3) {\it{Inter-layer combination}} emphasizes the effect of different propagation ranges (\emph{i.e.}, the number of GNN layers) on node representation learning. All these three aspects come to the same destination: boosting the expressive ability of GNNs for heterophilic graphs by encouraging distinguishable and discriminative node representations.
\subsubsection{Adaptive Message Aggregation}
Given the neighbors to be aggregated, the key of integrating beneficial messages on heterophilic graphs is distinguishing the information of similar neighbors (likely in the same class) from that of dissimilar neighbors (likely in different classes). To make node representations on heterophilic graphs more discriminative, adaptive message aggregation methods alter the aggregation operation $\operatorname{AGGREGATE}(\cdot)$ by imposing adaptive edge-aware weights $a_{uv}^{(l)}$ for node pair $(u,v)$ at the $l$-th layer as:
\begin{equation}
\label{eq:new_aggr}
\mathbf{m}^{(l)}_v  = \operatorname{AGGREGATE}^{(l)}(\{a_{uv}^{(l)}\,\mathbf{h}^{(l-1)}_u: u \in \mathcal{N}(v)\}).
\end{equation}
In this way, different methods develop various weight assignment schemes for $a_{uv}^{(l)}$ to model the importance of similar and dissimilar neighbors during aggregation. In the following, we provide the details of weight assignment schemes adopted by existing methods in the \textit{spectral} domain and the \textit{spatial} domain, respectively. To be concrete, spectral GNNs leverage the theory of graph signal processing to design graph filters, and spatial GNNs focus on the graph structural topology to develop aggregation strategies.

In spectral domain, in contrast to Laplacian smoothing~\cite{li2018deeper} and low-pass filtering~\cite{sgc_wu2019simplifying} to approximate graph Fourier transformation on homophilic graphs, spectral GNNs on heterophilic graphs involve both low-pass and high-pass filters to adaptively extract low-frequency and high-frequency graph signals. The essential intuition behind this lies in that low-pass filters mainly retain the commonality of node features, while high-pass filters capture the difference between nodes.

Typically, FAGCN~\cite{fagcn_bo2021beyond} adopts a self-gating attention mechanism to learn the proportion of low-frequency and high-frequency signals by splitting the $a_{uv}^{(l)}$ into two components, \emph{i.e.}, $a_{uv}^{(l,LP)}$ and $a_{uv}^{(l,HP)}$, corresponding to low-pass and high-pass filters, respectively. Through adaptive frequency signal learning, FAGCN could achieve expressive performance on different types of graphs with homophily and heterophily. Apart from low-pass and high-pass filters, ACM~\cite{acm_luan2021heterophily} further involves the identity filter, which is the linear combination of low-pass and high-pass filters. In this way, ACM could adaptively exploit beneficial neighbor information from different filter channels for each node; Meanwhile, its identity filter could guarantee less information loss of the input signal.

In spatial domain, heterophilic GNNs require the diverse topology-based aggregation of neighbors from the same or different classes, rather than the average aggregation in homophily GNNs. Therefore, the edge-aware weights of neighbors should be assigned according to the spatial graph topology and node labels. Taking node attributes as weak labels, DMP method~\cite{yang2021diverse} considers node attribute heterophily for diverse message passing and specifies every attribute propagation weight on each edge. Instead of the scalar weight $a_{uv}^{(l)}$ that aggregates all the node attributes with the same weight at the node level, DMP extends the weight to a vector ${\bf{a}}_{uv}^{(l)}$ through operating in the attribute dimension, and this vector can be calculated by either relaxing GAT~\cite{velivckovic2018graph} weights to real values or allowing an element-wise average of neighbor weights.
In contrast, WRGNN~\cite{SureshBNLM21} first transforms the original input heterophilic graph to a multi-relational graph that models the heterophily in relational edges, followed by relational aggregation with explicit link weights.

Apart from the adaptive edge-aware weight learning, there is another solution working on the neighbor representation learning by revising $\mathbf{h}^{(l-1)}_u$ in Eq.~(\ref{eq:new_aggr}). Conventionally, the above-mentioned methods mainly utilize the contextual node representations of neighbors; In contrast, this solution transforms contextual node embeddings $\mathbf{h}^{(l-1)}_u$ to other node-level properties that reflect the heterophily. In this way, heterophilic GNNs could capture the beneficial information of heterophily for distinguishable node representation learning. Typically, instead of propagating original node feature representations, CPGNN~\cite{zhu2021graph} propagates a prior belief estimation based on a compatibility matrix, so that it could capture both heterophily and homophily by modeling the likelihood of connections between nodes in different classes. Besides, GGCN~\cite{yan2021two} uses the cosine similarity to send signed neighbor features under certain constraints of relative node degrees. In this way, the messages are allowed to be optionally multiplied by a negative sign or a positive sign. Intuitively, signed messages consist of the negated messages sent by neighbors of the opposing classes, and the positive messages sent by neighbors of the same class. Going beyond the uniform GCN aggregation, NLGNN~\cite{Liu2021NLGNN} and GPNN~\cite{yang2021graph} consider the sequential aggregation where the neighbors are ranked based on the class similarity in order. A regular 1D-convolution layer is applied to extract the affinities between the sequential nodes whether the nodes are close or distant in heterophilic graphs.

\subsubsection{Ego-neighbor Separation}
On heterophilic graphs, an ego node is likely to be dissimilar with its neighbors in terms of class labels. Hence, encoding ego-node representations separately from the aggregated representations of neighbor nodes would benefit distinguishable node embedding learning. In detail, ego-neighbor separation methods detach self-loop connections of the ego nodes in $\operatorname{AGGREGATE}(\cdot)$. Meanwhile, they alter the $\operatorname{UPDATE}(\cdot)$ as the non-mixing operations, \emph{e.g.}, concatenation, instead of the mixing operation, \emph{e.g.}, ``average'' in vanilla GCN.

H2GCN~\cite{h2gcn_zhu2020beyond} first proposes to exclude the self-loop connection and points out that the non-mixing operations in the update function ensure that expressive node representations would survive over multiple rounds of propagation without becoming prohibitively similar. Besides, WRGNN~\cite{SureshBNLM21} imposes different mapping functions on the ego-node embedding and its neighbor aggregated messages, while GGCN~\cite{yan2021two} simplifies the mapping functions to learnable scalar parameters to separately learn ego-neighbor representations. Moreover, ACM~\cite{acm_luan2021heterophily} adopts the identity filter to separate the ego embedding and then conducts the channel-level combination with its neighbor information in the update function.

\begin{comment}
\subsubsection{Adaptive Message Aggregation}
To make node representations on heterophilic graphs more discriminative, adaptive message aggregation methods reconsider the aggregation operation $\operatorname{AGGREGATE}(\cdot)$. Specifically, given the neighbors to be aggregated, the key of extracting beneficial messages on heterophilic graphs for node classification is distinguishing the information of similar neighbors (likely in the same class) from that of dissimilar neighbors (unlikely to be in the same class).

To achieve this, one solution is to arrange adaptive edge-aware weights into the aggregation function:
\begin{equation}
\label{eq:new_aggr}
\mathbf{m}^{(l)}_v  = \operatorname{AGGREGATE}^{(l)}(\{a_{uv}^{(l)}\,\mathbf{h}^{(l-1)}_u: u \in \mathcal{N}(v)\}),
\end{equation}

\noindent where the edge weight between node $u$ and $v$ at the $l$-th layer is indicated $a_{uv}^{(l)}$.
By customizing various weight assignment schemes of $a_{uv}^{(l)}$, the importance of different neighbors are considered during aggregation.
Existing methods have attempted to find solutions from both spectral domain and spatial domain, where spectral GNNs leverage the theory of graph signal processing for designing graph filters, and spatial GNNs focus on the design of aggregation mechanism through the graph structural topology.

In spectral domain, GNNs on homophilic graphs generally conduct Laplacian smoothing~\cite{li2018deeper} and low-pass filtering~\cite{sgc_wu2019simplifying} to approximate graph Fourier transformation. In contrast, spectral GNNs on heterophilic graphs involve both low-passing and high-passing filters to adaptively extract low-frequency and high-frequency graph signals. The essential intuition behind this lies in that low-pass filters mainly retain the commonality of node features, while high-pass filters capture the difference between nodes.
Typically, FAGCN~\cite{fagcn_bo2021beyond} adopts a self-gating attention mechanism to learn the proportion of low-frequency and high-frequency signals by splitting the $a_{uv}^{(l)}$ into two components, \emph{i.e.}, $a_{uv}^{(l,L)}$ and $a_{uv}^{(l,H)}$, corresponding to low-pass and high-pass filters, respectively. Through adaptive frequency signal learning, FAGCN could achieve expressive performance on different types of graphs with homophily and heterophily. Besides low-pass and high-pass filters, ACM~\cite{acm_luan2021heterophily} further involves the identity filter in the set of filterbanks, where the identity filter can be taken as the linear combination of low-pass and high-pass filters. In this way, ACM could adaptively exploit beneficial neighbor information from different filter channels for each node, and in the meanwhile, there would not be much information loss of the input signal.

In spatial domain, heterophilic GNNs require the diverse aggregation of neighbors from the same or different classes, rather than the average aggregation in homophily GNNs. This means that the edge-aware weights of different neighbors for the ego nodes should be assigned according to the spatial graph topology and node labels. Taking node attributes as weak labels, DMP method~\cite{yang2021diverse} considers node attribute heterophily for diverse message passing and specifies every attribute propagation weight on each edge. Instead of the scalar weight $a_{uv}^{(l)}$ that aggregates all the node attributes with the same weight at the node level, DMP extends the weight to a vector ${\bf{a}}_{uv}^{(l)}$ through operating in the attribute dimension, and this vector can be calculated by either relaxing GAT~\cite{velivckovic2018graph} weights to real values or allowing an element-wise average of neighbor weights. Besides, WRGNN~\cite{SureshBNLM21} first transform the original input heterophilic graphs to a multi-relational graph that models the heterophily in relational edges, followed by relational aggregation with explicit link weights.

Instead of merely counting on the contextual node representations of neighbors, another solution is to transform contextual node embeddings to other node-level properties reflecting the heterophily. In this way, heterophilic GNNs could capture the beneficial information of the characteristic of heterophily for distinguishable node representation learning. In light of this, in contrast to propagating original node feature representations, CPGNN~\cite{zhu2021graph} propagates a prior belief estimation based on a compatibility matrix that captures both heterophily and homophily by modeling the likelihood of connections between nodes in different classes. Besides, GGCN~\cite{yan2021two} uses the cosine similarity to send signed neighbor features under certain constraints of relative node degrees, so that the messages are allowed to be optionally multiplied by a negative sign or a positive sign. Intuitively, signed messages consist of the negated messages sent by neighbors of the opposing classes, and the positive messages sent by neighbors of the same class. In contrast to the above methods, NLGNN~\cite{Liu2021NLGNN} and GPNN~\cite{yang2021graph} go beyond the uniform message passing aggregation and consider the sequential aggregation where the neighbors are ranked based on the class similarity in order. A regular 1D-convolution layer is applied to extract the affinities between the sequential nodes wherever the nodes are close or distant in heterophilic graphs.
\end{comment}
\begin{comment}
\subsubsection{Ego-neighbor Separation} Under the heterophily setting of graphs, an ego node is likely to be dissimilar with its neighbors in terms of class labels, hence, encoding ego-node representations separately from the aggregated representations of neighbor nodes would benefit distinguishable node embedding learning. In detail, in Eq.~\ref{eq:GNN}, the message vector $\mathbf{m}^{(l)}_v$ should be calculated without the self-loop, \emph{i.e.}, $v \notin \mathcal{N}(v)$, and $\mathbf{h}^{(l)}_{v}$ should be separately considered with $\mathbf{m}^{(l)}_v$ in the update function.

H2GCN~\cite{h2gcn_zhu2020beyond} first proposes this strategy and points out that $\operatorname{UPDATE}(\cdot)$ should be critically defined with non-mixing operations, \emph{e.g.}, concatenation, instead of average mixing in vanilla GCN, so that expressive node representations would survive over multiple rounds of propagation without becoming prohibitively similar. Besides, WRGNN~\cite{SureshBNLM21} imposes different mapping functions on the ego-node embedding and its neighbor aggregated messages, while GGCN~\cite{yan2021two} simplifies the mapping functions to learnable scalar parameters to separately learning ego-neighbor representations. In contrast, ACM~\cite{acm_luan2021heterophily} adopts the identity filter to separate the ego-embedding and further conducts channel-level combination with its neighbor information in the update function.
\end{comment}

\subsubsection{Inter-layer Combination} Different from adaptive message aggregation methods and ego-neighbor separation methods which deal with heterophilic graphs by looking deeply into each layer of GNNs, inter-layer combination methods consider the layer-wise operations to boost the representation power of GNNs under heterophily. The intuition behind this strategy is that in the shallow layers of GNNs, they collect local information, \emph{e.g.}, one-hop neighbor locality in two-layer vanilla GCN, when the layers go deeper, GNNs gradually capture global information implicitly via multiple rounds of neighbor propagation. Under the heterophily setting, neighbors with similar information, \emph{i.e.}, class labels, might locate in both local geometry and long-term global topology. Hence, combining intermediate representations from each layer contributes to leveraging different neighbor ranges with the consideration of both local and global structural properties, resulting in powerful heterophilic GNNs.

The prior idea first comes from JKNet~\cite{xu2018representation} which flexibly captures better structure-aware representation with different neighborhood ranges under the homophily setting. Due to the more complex structural topology in heterophilic graphs, H2GCN~\cite{h2gcn_zhu2020beyond} is inspired to concatenate the node representations from all previous layers and learn heterophilic node features at the final layer distinctly. Compared with H2GCN using all previous intermediate representations, GCNII~\cite{chen2020simple} only integrates the first layer's node embedding at each layer with the initial residual connection. Instead of using the simple concatenation operation, GPR-GNN~\cite{chien2020adaptive} further assigns learnable weights to combine the representations of each layer adaptively via the Generalized PageRank (GPR) technique. Hence, inter-layer combination methods are able to conduct topological feature exploration and benefit from informative multi-round propagation, making node features of heterophilic graphs distinguishable.
\begin{comment}
\begin{figure}[!t]
  \centering
  \includegraphics[width=0.38\textwidth]{figs/statistics.png}
  \caption{Statistics of techniques in heterophilic GNNs.}
  \label{fig:stats}
  \vspace{-2mm}
\end{figure}
\end{comment}

\section{Introduction}

The {\it IJCAI--22 Proceedings} will be printed from electronic
manuscripts submitted by the authors. These must be PDF ({\em Portable
Document Format}) files formatted for 8-1/2$''$ $\times$ 11$''$ paper.

\subsection{Length of Papers}

All paper {\em submissions} must have a maximum of six pages, plus at most one for references. The seventh page cannot contain {\bf anything} other than references.

The length rules may change for final camera-ready versions of accepted papers and will differ between tracks. Some tracks may include only references in the last page, whereas others allow for any content in all pages. Similarly, some tracks allow you to buy a few extra pages should you want to, whereas others don't.

If your paper is accepted, please carefully read the notifications you receive, and check the proceedings submission information website\footnote{\url{https://proceedings.ijcai.org/info}} to know how many pages you can finally use. That website holds the most up-to-date information regarding paper length limits at all times. Please notice that if your track allows for a special references-only page, the {\bf references-only page(s) cannot contain anything else than references} (i.e.: do not write your acknowledgments on that page or you will be charged for it).

\subsection{Word Processing Software}

As detailed below, IJCAI has prepared and made available a set of
\LaTeX{} macros and a Microsoft Word template for use in formatting
your paper. If you are using some other word processing software, please follow the format instructions given below and ensure that your final paper looks as much like this sample as possible.

\section{Style and Format}

\LaTeX{} and Word style files that implement these instructions
can be retrieved electronically. (See Appendix~\ref{stylefiles} for
instructions on how to obtain these files.)

\subsection{Layout}

Print manuscripts two columns to a page, in the manner in which these
instructions are printed. The exact dimensions for pages are:
\begin{itemize}
\item left and right margins: .75$''$
\item column width: 3.375$''$
\item gap between columns: .25$''$
\item top margin---first page: 1.375$''$
\item top margin---other pages: .75$''$
\item bottom margin: 1.25$''$
\item column height---first page: 6.625$''$
\item column height---other pages: 9$''$
\end{itemize}

All measurements assume an 8-1/2$''$ $\times$ 11$''$ page size. For
A4-size paper, use the given top and left margins, column width,
height, and gap, and modify the bottom and right margins as necessary.

\subsection{Format of Electronic Manuscript}

For the production of the electronic manuscript, you must use Adobe's
{\em Portable Document Format} (PDF). A PDF file can be generated, for
instance, on Unix systems using {\tt ps2pdf} or on Windows systems
using Adobe's Distiller. There is also a website with free software
and conversion services: \url{http://www.ps2pdf.com}. For reasons of
uniformity, use of Adobe's {\em Times Roman} font is strongly suggested.
In \LaTeX2e{} this is accomplished by writing
\begin{quote}
\mbox{\tt $\backslash$usepackage\{times\}}
\end{quote}
in the preamble.\footnote{You may want also to use the package {\tt
latexsym}, which defines all symbols known from the old \LaTeX{}
version.}

Additionally, it is of utmost importance to specify the {\bf
letter} format (corresponding to 8-1/2$''$ $\times$ 11$''$) when
formatting the paper. When working with {\tt dvips}, for instance, one
should specify {\tt -t letter}.

\subsection{Title and Author Information}

Center the title on the entire width of the page in a 14-point bold
font. The title must be capitalized using Title Case. Below it, center author name(s) in 12-point bold font. On the following line(s) place the affiliations, each affiliation on its own line using 12-point regular font. Matching between authors and affiliations can be done using numeric superindices. Optionally, a comma-separated list of email addresses follows the affiliation(s) line(s), using 12-point regular font.

\subsubsection{Blind Review}

In order to make blind reviewing possible, authors must omit their
names and affiliations when submitting the paper for review. In place
of names and affiliations, provide a list of content areas. When
referring to one's own work, use the third person rather than the
first person. For example, say, ``Previously,
Gottlob~\shortcite{gottlob:nonmon} has shown that\ldots'', rather
than, ``In our previous work~\cite{gottlob:nonmon}, we have shown
that\ldots'' Try to avoid including any information in the body of the
paper or references that would identify the authors or their
institutions. Such information can be added to the final camera-ready
version for publication.

\subsection{Abstract}

Place the abstract at the beginning of the first column 3$''$ from the
top of the page, unless that does not leave enough room for the title
and author information. Use a slightly smaller width than in the body
of the paper. Head the abstract with ``Abstract'' centered above the
body of the abstract in a 12-point bold font. The body of the abstract
should be in the same font as the body of the paper.

The abstract should be a concise, one-paragraph summary describing the
general thesis and conclusion of your paper. A reader should be able
to learn the purpose of the paper and the reason for its importance
from the abstract. The abstract should be no more than 200 words long.

\subsection{Text}

The main body of the text immediately follows the abstract. Use
10-point type in a clear, readable font with 1-point leading (10 on
11).

Indent when starting a new paragraph, except after major headings.

\subsection{Headings and Sections}

When necessary, headings should be used to separate major sections of
your paper. (These instructions use many headings to demonstrate their
appearance; your paper should have fewer headings.). All headings should be capitalized using Title Case.

\subsubsection{Section Headings}

Print section headings in 12-point bold type in the style shown in
these instructions. Leave a blank space of approximately 10 points
above and 4 points below section headings.  Number sections with
arabic numerals.

\subsubsection{Subsection Headings}

Print subsection headings in 11-point bold type. Leave a blank space
of approximately 8 points above and 3 points below subsection
headings. Number subsections with the section number and the
subsection number (in arabic numerals) separated by a
period.

\subsubsection{Subsubsection Headings}

Print subsubsection headings in 10-point bold type. Leave a blank
space of approximately 6 points above subsubsection headings. Do not
number subsubsections.

\paragraph{Titled paragraphs.} You should use titled paragraphs if and
only if the title covers exactly one paragraph. Such paragraphs should be
separated from the preceding content by at least 3pt, and no more than
6pt. The title should be in 10pt bold font and ended with a period.
After that, a 1em horizontal space should follow the title before
the paragraph's text.

In \LaTeX{} titled paragraphs should be typeset using
\begin{quote}
{\tt \textbackslash{}paragraph\{Title.\} text} .
\end{quote}

\subsubsection{Acknowledgements}

You may include an unnumbered acknowledgments section, including
acknowledgments of help from colleagues, financial support, and
permission to publish. If present, acknowledgements must be in a dedicated,
unnumbered section appearing after all regular sections but before any
appendices or references.

Use
\begin{quote}
    {\tt \textbackslash{}section*\{Acknowledgements\}})
\end{quote}
to typeset the acknowledgements section in \LaTeX{}.

\subsubsection{Appendices}

Any appendices directly follow the text and look like sections, except
that they are numbered with capital letters instead of arabic
numerals. See this document for an example.

\subsubsection{References}

The references section is headed ``References'', printed in the same
style as a section heading but without a number. A sample list of
references is given at the end of these instructions. Use a consistent
format for references. The reference list should not include publicly unavailable work.

\subsection{Citations}

Citations within the text should include the author's last name and
the year of publication, for example~\cite{gottlob:nonmon}.  Append
lowercase letters to the year in cases of ambiguity.  Treat multiple
authors as in the following examples:~\cite{abelson-et-al:scheme}
or~\cite{bgf:Lixto} (for more than two authors) and
\cite{brachman-schmolze:kl-one} (for two authors).  If the author
portion of a citation is obvious, omit it, e.g.,
Nebel~\shortcite{nebel:jair-2000}.  Collapse multiple citations as
follows:~\cite{gls:hypertrees,levesque:functional-foundations}.
\nocite{abelson-et-al:scheme}
\nocite{bgf:Lixto}
\nocite{brachman-schmolze:kl-one}
\nocite{gottlob:nonmon}
\nocite{gls:hypertrees}
\nocite{levesque:functional-foundations}
\nocite{levesque:belief}
\nocite{nebel:jair-2000}

\subsection{Footnotes}

Place footnotes at the bottom of the page in a 9-point font.  Refer to
them with superscript numbers.\footnote{This is how your footnotes
should appear.} Separate them from the text by a short
line.\footnote{Note the line separating these footnotes from the
text.} Avoid footnotes as much as possible; they interrupt the flow of
the text.

\section{Illustrations}

Place all illustrations (figures, drawings, tables, and photographs)
throughout the paper at the places where they are first discussed,
rather than at the end of the paper.

They should be floated to the top (preferred) or bottom of the page,
unless they are an integral part
of your narrative flow. When placed at the bottom or top of
a page, illustrations may run across both columns, but not when they
appear inline.

Illustrations must be rendered electronically or scanned and placed
directly in your document. They should be cropped outside \LaTeX{},
otherwise portions of the image could reappear during the post-processing of your paper.
When possible, generate your illustrations in a vector format.
When using bitmaps, please use 300dpi resolution at least.
All illustrations should be understandable when printed in black and
white, albeit you can use colors to enhance them. Line weights should
be 1/2-point or thicker. Avoid screens and superimposing type on
patterns, as these effects may not reproduce well.

Number illustrations sequentially. Use references of the following
form: Figure 1, Table 2, etc. Place illustration numbers and captions
under illustrations. Leave a margin of 1/4-inch around the area
covered by the illustration and caption.  Use 9-point type for
captions, labels, and other text in illustrations. Captions should always appear below the illustration.

\section{Tables}

Tables are considered illustrations containing data. Therefore, they should also appear floated to the top (preferably) or bottom of the page, and with the captions below them.

\begin{table}
\centering
\begin{tabular}{lll}
\hline
Scenario  & $\delta$ & Runtime \\
\hline
Paris       & 0.1s  & 13.65ms     \\
Paris       & 0.2s  & 0.01ms      \\
New York    & 0.1s  & 92.50ms     \\
Singapore   & 0.1s  & 33.33ms     \\
Singapore   & 0.2s  & 23.01ms     \\
\hline
\end{tabular}
\caption{Latex default table}
\label{tab:plain}
\end{table}

\begin{table}
\centering
\begin{tabular}{lrr}
\toprule
Scenario  & $\delta$ (s) & Runtime (ms) \\
\midrule
Paris       & 0.1  & 13.65      \\
            & 0.2  & 0.01       \\
New York    & 0.1  & 92.50      \\
Singapore   & 0.1  & 33.33      \\
            & 0.2  & 23.01      \\
\bottomrule
\end{tabular}
\caption{Booktabs table}
\label{tab:booktabs}
\end{table}

If you are using \LaTeX, you should use the {\tt booktabs} package, because it produces better tables than the standard ones. Compare Tables \ref{tab:plain} and~\ref{tab:booktabs}. The latter is clearly more readable for three reasons:

\begin{enumerate}
    \item The styling is better thanks to using the {\tt booktabs} rulers instead of the default ones.
    \item Numeric columns are right-aligned, making it easier to compare the numbers. Make sure to also right-align the corresponding headers, and to use the same precision for all numbers.
    \item We avoid unnecessary repetition, both between lines (no need to repeat the scenario name in this case) as well as in the content (units can be shown in the column header).
\end{enumerate}

\section{Formulas}

IJCAI's two-column format makes it difficult to typeset long formulas. A usual temptation is to reduce the size of the formula by using the {\tt small} or {\tt tiny} sizes. This doesn't work correctly with the current \LaTeX{} versions, breaking the line spacing of the preceding paragraphs and title, as well as the equation number sizes. The following equation demonstrates the effects (notice that this entire paragraph looks badly formatted):
\begin{tiny}
\begin{equation}
    x = \prod_{i=1}^n \sum_{j=1}^n j_i + \prod_{i=1}^n \sum_{j=1}^n i_j + \prod_{i=1}^n \sum_{j=1}^n j_i + \prod_{i=1}^n \sum_{j=1}^n i_j + \prod_{i=1}^n \sum_{j=1}^n j_i
\end{equation}
\end{tiny}%

Reducing formula sizes this way is strictly forbidden. We {\bf strongly} recommend authors to split formulas in multiple lines when they don't fit in a single line. This is the easiest approach to typeset those formulas and provides the most readable output%
\begin{align}
    x =& \prod_{i=1}^n \sum_{j=1}^n j_i + \prod_{i=1}^n \sum_{j=1}^n i_j + \prod_{i=1}^n \sum_{j=1}^n j_i + \prod_{i=1}^n \sum_{j=1}^n i_j + \nonumber\\
    + & \prod_{i=1}^n \sum_{j=1}^n j_i
\end{align}%

If a line is just slightly longer than the column width, you may use the {\tt resizebox} environment on that equation. The result looks better and doesn't interfere with the paragraph's line spacing: %
\begin{equation}
\resizebox{.91\linewidth}{!}{$
    \displaystyle
    x = \prod_{i=1}^n \sum_{j=1}^n j_i + \prod_{i=1}^n \sum_{j=1}^n i_j + \prod_{i=1}^n \sum_{j=1}^n j_i + \prod_{i=1}^n \sum_{j=1}^n i_j + \prod_{i=1}^n \sum_{j=1}^n j_i
$}
\end{equation}%

This last solution may have to be adapted if you use different equation environments, but it can generally be made to work. Please notice that in any case:

\begin{itemize}
    \item Equation numbers must be in the same font and size as the main text (10pt).
    \item Your formula's main symbols should not be smaller than {\small small} text (9pt).
\end{itemize}

For instance, the formula
\begin{equation}
    \resizebox{.91\linewidth}{!}{$
    \displaystyle
    x = \prod_{i=1}^n \sum_{j=1}^n j_i + \prod_{i=1}^n \sum_{j=1}^n i_j + \prod_{i=1}^n \sum_{j=1}^n j_i + \prod_{i=1}^n \sum_{j=1}^n i_j + \prod_{i=1}^n \sum_{j=1}^n j_i + \prod_{i=1}^n \sum_{j=1}^n i_j
$}
\end{equation}
would not be acceptable because the text is too small.

\section{Examples, Definitions, Theorems and Similar}

Examples, definitions, theorems, corollaries and similar must be written in their own paragraph. The paragraph must be separated by at least 2pt and no more than 5pt from the preceding and succeeding paragraphs. They must begin with the kind of item written in 10pt bold font followed by their number (e.g.: Theorem 1), optionally followed by a title/summary between parentheses in non-bold font and ended with a period. After that the main body of the item follows, written in 10 pt italics font (see below for examples).

In \LaTeX{} We strongly recommend you to define environments for your examples, definitions, propositions, lemmas, corollaries and similar. This can be done in your \LaTeX{} preamble using \texttt{\textbackslash{newtheorem}} -- see the source of this document for examples. Numbering for these items must be global, not per-section (e.g.: Theorem 1 instead of Theorem 6.1).

\begin{example}[How to write an example]
Examples should be written using the example environment defined in this template.
\end{example}

\begin{theorem}
This is an example of an untitled theorem.
\end{theorem}

You may also include a title or description using these environments as shown in the following theorem.

\begin{theorem}[A titled theorem]
This is an example of a titled theorem.
\end{theorem}

\section{Proofs}

Proofs must be written in their own paragraph separated by at least 2pt and no more than 5pt from the preceding and succeeding paragraphs. Proof paragraphs should start with the keyword ``Proof." in 10pt italics font. After that the proof follows in regular 10pt font. At the end of the proof, an unfilled square symbol (qed) marks the end of the proof.

In \LaTeX{} proofs should be typeset using the \texttt{\textbackslash{proof}} environment.

\begin{proof}
This paragraph is an example of how a proof looks like using the \texttt{\textbackslash{proof}} environment.
\end{proof}

\section{Algorithms and Listings}

Algorithms and listings are a special kind of figures. Like all illustrations, they should appear floated to the top (preferably) or bottom of the page. However, their caption should appear in the header, left-justified and enclosed between horizontal lines, as shown in Algorithm~\ref{alg:algorithm}. The algorithm body should be terminated with another horizontal line. It is up to the authors to decide whether to show line numbers or not, how to format comments, etc.

In \LaTeX{} algorithms may be typeset using the {\tt algorithm} and {\tt algorithmic} packages, but you can also use one of the many other packages for the task.

\begin{algorithm}[tb]
\caption{Example algorithm}
\label{alg:algorithm}
\textbf{Input}: Your algorithm's input\\
\textbf{Parameter}: Optional list of parameters\\
\textbf{Output}: Your algorithm's output
\begin{algorithmic}[1]
\STATE Let $t=0$.
\WHILE{condition}
\STATE Do some action.
\IF {conditional}
\STATE Perform task A.
\ELSE
\STATE Perform task B.
\ENDIF
\ENDWHILE
\STATE \textbf{return} solution
\end{algorithmic}
\end{algorithm}

\section*{Acknowledgments}

The preparation of these instructions and the \LaTeX{} and Bib\TeX{}
files that implement them was supported by Schlumberger Palo Alto
Research, AT\&T Bell Laboratories, and Morgan Kaufmann Publishers.
Preparation of the Microsoft Word file was supported by IJCAI.  An
early version of this document was created by Shirley Jowell and Peter
F. Patel-Schneider.  It was subsequently modified by Jennifer
Ballentine and Thomas Dean, Bernhard Nebel, Daniel Pagenstecher,
Kurt Steinkraus, Toby Walsh and Carles Sierra. The current version
has been prepared by Marc Pujol-Gonzalez and Francisco Cruz-Mencia.

\section{Introduction}

\input{01introduction}

\section{Preliminary}

\input{02preliminary}

\section{GNNs with Heterophily}

\input{03mainbody}

\section{Real-World Benchmarks}

\input{04datasets}

\section{Future Directions}

\input{05future_directions}

\clearpage

\bibliographystyle{named}

redpajama_set_name: RedPajamaArXiv