Alias-Free GAN
This group of researchers consistently demonstrates a degree of empirical rigor that is unmatched across any other ML lab in industry or academia - remarkable empirical results as always, reproducible experiments, open-source and well-engineered codebase, and valuable insights about low-level learning dynamics and high-level emergent artifacts.  Applied ML wouldn&#x27;t have such a bad rap if more researchers held themselves to similar standards.