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Compressing Images by Encoding Their Latent Representations with
  Relative Entropy Coding

Compressing Images by Encoding Their Latent Representations with Relative Entropy Coding

2 October 2020
Gergely Flamich
Marton Havasi
José Miguel Hernández-Lobato
ArXivPDFHTML

Papers citing "Compressing Images by Encoding Their Latent Representations with Relative Entropy Coding"

15 / 15 papers shown
Title
Universal Exact Compression of Differentially Private Mechanisms
Universal Exact Compression of Differentially Private Mechanisms
Yanxiao Liu
Wei-Ning Chen
Ayfer Özgür
Cheuk Ting Li
47
2
0
28 May 2024
Accelerating Relative Entropy Coding with Space Partitioning
Accelerating Relative Entropy Coding with Space Partitioning
Jiajun He
Gergely Flamich
José Miguel Hernández-Lobato
28
1
0
20 May 2024
Some Notes on the Sample Complexity of Approximate Channel Simulation
Some Notes on the Sample Complexity of Approximate Channel Simulation
Gergely Flamich
Lennie Wells
32
3
0
07 May 2024
RECOMBINER: Robust and Enhanced Compression with Bayesian Implicit
  Neural Representations
RECOMBINER: Robust and Enhanced Compression with Bayesian Implicit Neural Representations
Carlos Rombaldo Junior
Ingolf Becker
Zongyu Guo
Shane Johnson
13
12
0
29 Sep 2023
Low-Entropy Latent Variables Hurt Out-of-Distribution Performance
Low-Entropy Latent Variables Hurt Out-of-Distribution Performance
Nandi Schoots
Dylan R. Cope
OODD
OOD
31
0
0
20 May 2023
Lossy Image Compression with Conditional Diffusion Models
Lossy Image Compression with Conditional Diffusion Models
Ruihan Yang
Stephan Mandt
DiffM
11
128
0
14 Sep 2022
Lossy Image Compression with Quantized Hierarchical VAEs
Lossy Image Compression with Quantized Hierarchical VAEs
Zhihao Duan
Ming Lu
Zhan Ma
F. Zhu
46
43
0
27 Aug 2022
Lossy Compression with Gaussian Diffusion
Lossy Compression with Gaussian Diffusion
Lucas Theis
Tim Salimans
Matthew D. Hoffman
Fabian Mentzer
DiffM
38
78
0
17 Jun 2022
Towards Empirical Sandwich Bounds on the Rate-Distortion Function
Towards Empirical Sandwich Bounds on the Rate-Distortion Function
Yibo Yang
Stephan Mandt
30
24
0
23 Nov 2021
Algorithms for the Communication of Samples
Algorithms for the Communication of Samples
Lucas Theis
Noureldin Yosri
55
40
0
25 Oct 2021
In-Network Learning: Distributed Training and Inference in Networks
In-Network Learning: Distributed Training and Inference in Networks
Matei Moldoveanu
Milad Sefidgaran
27
11
0
07 Jul 2021
On In-network learning. A Comparative Study with Federated and Split
  Learning
On In-network learning. A Comparative Study with Federated and Split Learning
Matei Moldoveanu
Milad Sefidgaran
FedML
24
7
0
30 Apr 2021
Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding
Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding
Yangjun Ruan
Karen Ullrich
Daniel de Souza Severo
James Townsend
Ashish Khisti
Arnaud Doucet
Alireza Makhzani
Chris J. Maddison
13
25
0
22 Feb 2021
Universally Quantized Neural Compression
Universally Quantized Neural Compression
E. Agustsson
Lucas Theis
MQ
19
89
0
17 Jun 2020
End-to-end optimization of nonlinear transform codes for perceptual
  quality
End-to-end optimization of nonlinear transform codes for perceptual quality
Johannes Ballé
Valero Laparra
Eero P. Simoncelli
72
244
0
18 Jul 2016
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