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. 2310.04935
  4. Cited By
Statistical Guarantees for Variational Autoencoders using PAC-Bayesian
  Theory

Statistical Guarantees for Variational Autoencoders using PAC-Bayesian Theory

7 October 2023
S. Mbacke
Florence Clerc
Pascal Germain
    DRL
ArXivPDFHTML

Papers citing "Statistical Guarantees for Variational Autoencoders using PAC-Bayesian Theory"

14 / 14 papers shown
Title
Multi-View Majority Vote Learning Algorithms: Direct Minimization of PAC-Bayesian Bounds
Multi-View Majority Vote Learning Algorithms: Direct Minimization of PAC-Bayesian Bounds
Mehdi Hennequin
Abdelkrim Zitouni
K. Benabdeslem
H. Elghazel
Yacine Gaci
56
0
0
09 Nov 2024
A Markov Random Field Multi-Modal Variational AutoEncoder
A Markov Random Field Multi-Modal Variational AutoEncoder
Fouad Oubari
M. Baha
Raphael Meunier
Rodrigue Décatoire
Mathilde Mougeot
61
0
0
18 Aug 2024
Online PAC-Bayes Learning
Online PAC-Bayes Learning
Maxime Haddouche
Benjamin Guedj
83
21
0
31 May 2022
Certifiably Robust Variational Autoencoders
Certifiably Robust Variational Autoencoders
Ben Barrett
A. Camuto
M. Willetts
Tom Rainforth
AAML
DRL
50
16
0
15 Feb 2021
NVAE: A Deep Hierarchical Variational Autoencoder
NVAE: A Deep Hierarchical Variational Autoencoder
Arash Vahdat
Jan Kautz
BDL
69
910
0
08 Jul 2020
Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural
  Networks
Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks
Mahyar Fazlyab
Alexander Robey
Hamed Hassani
M. Morari
George J. Pappas
87
457
0
12 Jun 2019
A Primer on PAC-Bayesian Learning
A Primer on PAC-Bayesian Learning
Benjamin Guedj
148
222
0
16 Jan 2019
Sorting out Lipschitz function approximation
Sorting out Lipschitz function approximation
Cem Anil
James Lucas
Roger C. Grosse
86
321
0
13 Nov 2018
PAC-Bayes and Domain Adaptation
PAC-Bayes and Domain Adaptation
Pascal Germain
Amaury Habrard
Franccois Laviolette
Emilie Morvant
74
24
0
17 Jul 2017
PAC-Bayesian Theory Meets Bayesian Inference
PAC-Bayesian Theory Meets Bayesian Inference
Pascal Germain
Francis R. Bach
Alexandre Lacoste
Simon Lacoste-Julien
68
183
0
27 May 2016
Unsupervised Representation Learning with Deep Convolutional Generative
  Adversarial Networks
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
Alec Radford
Luke Metz
Soumith Chintala
GAN
OOD
250
14,008
0
19 Nov 2015
Generating Sentences from a Continuous Space
Generating Sentences from a Continuous Space
Samuel R. Bowman
Luke Vilnis
Oriol Vinyals
Andrew M. Dai
Rafal Jozefowicz
Samy Bengio
DRL
108
2,360
0
19 Nov 2015
Semi-Supervised Learning with Deep Generative Models
Semi-Supervised Learning with Deep Generative Models
Diederik P. Kingma
Danilo Jimenez Rezende
S. Mohamed
Max Welling
GAN
SSL
BDL
85
2,740
0
20 Jun 2014
Testing the Manifold Hypothesis
Testing the Manifold Hypothesis
Charles Fefferman
S. Mitter
Hariharan Narayanan
146
533
0
01 Oct 2013
1