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Improving Multimodal Joint Variational Autoencoders through Normalizing
  Flows and Correlation Analysis

Improving Multimodal Joint Variational Autoencoders through Normalizing Flows and Correlation Analysis

19 May 2023
Agathe Senellart
Clément Chadebec
S. Allassonnière
    DRL
ArXivPDFHTML

Papers citing "Improving Multimodal Joint Variational Autoencoders through Normalizing Flows and Correlation Analysis"

4 / 4 papers shown
Title
A survey of multimodal deep generative models
A survey of multimodal deep generative models
Masahiro Suzuki
Y. Matsuo
SyDa
DRL
43
75
0
05 Jul 2022
Pythae: Unifying Generative Autoencoders in Python -- A Benchmarking Use
  Case
Pythae: Unifying Generative Autoencoders in Python -- A Benchmarking Use Case
Clément Chadebec
Louis J. Vincent
S. Allassonnière
DRL
22
27
0
16 Jun 2022
Image-to-Image Translation with Conditional Adversarial Networks
Image-to-Image Translation with Conditional Adversarial Networks
Phillip Isola
Jun-Yan Zhu
Tinghui Zhou
Alexei A. Efros
SSeg
203
19,191
0
21 Nov 2016
MCMC using Hamiltonian dynamics
MCMC using Hamiltonian dynamics
Radford M. Neal
127
3,260
0
09 Jun 2012
1