Research map / Probabilistic and scientific modeling / Variational and generative sampling
iFlow: Numerically Invertible Flows for Efficient Lossless Compression via a Uniform Coder
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| replace rANS coder (LBB) with UBCS uniform coder in flow compression | Flow++ on CIFAR10 · CIFAR10 encoding | coding time (ms): 116 -> 21.0 | Helped |
| replace LBB local bits-back numerical-error coding with MST + UBCS | Flow++ · CIFAR10 | bits per dimension: 3.118 -> 3.118 | No clear effect |
| replace iVPF's own coding with iFlow MST + UBCS on the iVPF architecture | iVPF architecture · CIFAR10 | bits per dimension: 3.201 -> 3.196 | Helped |
| replace LBB with iFlow | Flow++ · CIFAR10 | auxiliary bits: 39.86 -> 34.28 | Helped |
| replace iVPF coding with iFlow | iVPF architecture · CIFAR10 | auxiliary bits: 6.00 -> 7.00 | Hurt |
| replace rANS with UBCS entropy coder | entropy coder · coding bandwidth, 1 thread encoder | M symbol/s: 5.1 -> 380 | Helped |
| replace iVPF with iFlow when testing on ImageNet32-trained model | generalization · CIFAR10 | bits per dimension: 3.49 -> 3.36 | Helped |
Closest papers by meaning
- Integer Discrete Flows and Lossless Compression (NeurIPS 2019 · similarity 0.88)
- IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression (ICLR 2021 · similarity 0.88)
- iVPF: Numerical Invertible Volume Preserving Flow for Efficient Lossless Compression (CVPR 2021 · similarity 0.87)
- Approaching Rate-Distortion Limits in Neural Compression with Lattice Transform Coding (ICLR 2025 · similarity 0.85)
- Lossy Compression with Pretrained Diffusion Models (ICLR 2025 · similarity 0.84)
- MeLLoC: Lossless Compression with High-order Mechanism Learning (NeurIPS 2024 · similarity 0.84)
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