1 citations · 1 across the 3 of their papers we have counts for
4 papers
Continuous First, Discrete Later: VQ-VAEs Without Dimensional Collapse
Xinyu Zhao, Nikita Karagodin, Hamed Hassani +3
While many approaches to improve VQ-VAE performance focus on codebook size and utilization, the effect of dimensional collapse, where trained VQ-VAE representations live in an extr…
Optimal Neural Compressors for the Rate-Distortion-Perception Tradeoff
Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti
Recent efforts in neural compression have focused on the rate-distortion-perception (RDP) tradeoff, where the perception constraint ensures the source and reconstruction distributi…
Approaching Rate-Distortion Limits in Neural Compression with Lattice Transform Coding
Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti
Neural compression has brought tremendous progress in designing lossy compressors with good rate-distortion (RD) performance at low complexity. Thus far, neural compression design…
Score-Based Methods for Discrete Optimization in Deep Learning
Eric Lei, Arman Adibi, Hamed Hassani
Discrete optimization problems often arise in deep learning tasks, despite the fact that neural networks typically operate on continuous data. One class of these problems involve o…