ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2010.01185
  4. Cited By
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"

14 / 14 papers shown
Title
Channel-wise Autoregressive Entropy Models for Learned Image Compression
Channel-wise Autoregressive Entropy Models for Learned Image Compression
David C. Minnen
Saurabh Singh
65
409
0
17 Jul 2020
Variational Bayesian Quantization
Variational Bayesian Quantization
Yibo Yang
Robert Bamler
Stephan Mandt
BDL
MQ
47
5
0
18 Feb 2020
HiLLoC: Lossless Image Compression with Hierarchical Latent Variable
  Models
HiLLoC: Lossless Image Compression with Hierarchical Latent Variable Models
James Townsend
Thomas Bird
Julius Kunze
David Barber
BDL
VLM
116
56
0
20 Dec 2019
Compression with Flows via Local Bits-Back Coding
Compression with Flows via Local Bits-Back Coding
Jonathan Ho
Evan Lohn
Pieter Abbeel
64
53
0
21 May 2019
Integer Discrete Flows and Lossless Compression
Integer Discrete Flows and Lossless Compression
Emiel Hoogeboom
Jorn W. T. Peters
Rianne van den Berg
Max Welling
72
159
0
17 May 2019
Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with
  Hierarchical Latent Variables
Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent Variables
F. Kingma
Pieter Abbeel
Jonathan Ho
52
97
0
16 May 2019
Practical Lossless Compression with Latent Variables using Bits Back
  Coding
Practical Lossless Compression with Latent Variables using Bits Back Coding
James Townsend
Thomas Bird
David Barber
DRL
64
142
0
15 Jan 2019
Minimal Random Code Learning: Getting Bits Back from Compressed Model
  Parameters
Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters
Marton Havasi
Robert Peharz
José Miguel Hernández-Lobato
48
80
0
30 Sep 2018
Joint Autoregressive and Hierarchical Priors for Learned Image
  Compression
Joint Autoregressive and Hierarchical Priors for Learned Image Compression
David C. Minnen
Johannes Ballé
G. Toderici
67
1,269
0
08 Sep 2018
Lossy Image Compression with Compressive Autoencoders
Lossy Image Compression with Compressive Autoencoders
Lucas Theis
Wenzhe Shi
Andrew Cunningham
Ferenc Huszár
62
1,054
0
01 Mar 2017
End-to-end Optimized Image Compression
End-to-end Optimized Image Compression
Johannes Ballé
Valero Laparra
Eero P. Simoncelli
DRL
77
1,704
0
05 Nov 2016
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
93
244
0
18 Jul 2016
Improving Variational Inference with Inverse Autoregressive Flow
Improving Variational Inference with Inverse Autoregressive Flow
Diederik P. Kingma
Tim Salimans
Rafal Jozefowicz
Xi Chen
Ilya Sutskever
Max Welling
BDL
DRL
105
1,816
0
15 Jun 2016
Auto-Encoding Variational Bayes
Auto-Encoding Variational Bayes
Diederik P. Kingma
Max Welling
BDL
408
16,947
0
20 Dec 2013
1