4.2 EMPIRICAL EVALUATION
Bringing together expressive PCs (i.e., HCLTs) and our (de)compressor, we proceed to evaluate the
compression performance of the proposed PC-based algorithm. We compare with 5 competitive
lossless compression algorithm: JPEG2000 (Christopoulos et al., 2000); WebP; IDF (Hoogeboom
et al., 2019), a Flow-based lossless compression algorithm; BitSwap (Kingma et al., 2019), BB-ANS
(Townsend et al., 2018), and McBits (Ruan et al., 2021), three VAE-based lossless compression meth-
ods. All 6 methods were tested on 4 datasets, which include MNIST (Deng, 2012), FashionMNIST

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Z1Z2Z3X1Z4X2X3X4X1X2X3X4Z1Z2Z3Z4ReplaceXibyZiAttachXibacktoZi(a)(b)(c)(d)X1X1X3X3X2X2X4X4Z3Z1Z2Z4EquivalentPublished as a conference paper at ICLR 2022
LOSSLESS COMPRESSION WITH PROBABILISTIC CIRCUITS