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Towards a Theoretical Understanding of the Robustness of Variational
  Autoencoders

Towards a Theoretical Understanding of the Robustness of Variational Autoencoders

14 July 2020
A. Camuto
M. Willetts
Stephen J. Roberts
Chris Holmes
Tom Rainforth
    AAML
    DRL
ArXivPDFHTML

Papers citing "Towards a Theoretical Understanding of the Robustness of Variational Autoencoders"

5 / 5 papers shown
Title
Support is All You Need for Certified VAE Training
Support is All You Need for Certified VAE Training
Changming Xu
Debangshu Banerjee
Deepak Vasisht
Gagandeep Singh
AAML
44
0
0
16 Apr 2025
Prototypical Self-Explainable Models Without Re-training
Prototypical Self-Explainable Models Without Re-training
Srishti Gautam
Ahcène Boubekki
Marina M.-C. Höhne
Michael C. Kampffmeyer
34
2
0
13 Dec 2023
Flow Matching in Latent Space
Flow Matching in Latent Space
Quan Dao
Hao Phung
Binh Duc Nguyen
Anh Tran
37
60
0
17 Jul 2023
Alleviating Adversarial Attacks on Variational Autoencoders with MCMC
Alleviating Adversarial Attacks on Variational Autoencoders with MCMC
Anna Kuzina
Max Welling
Jakub M. Tomczak
AAML
DRL
31
12
0
18 Mar 2022
Diagnosing Vulnerability of Variational Auto-Encoders to Adversarial
  Attacks
Diagnosing Vulnerability of Variational Auto-Encoders to Adversarial Attacks
Anna Kuzina
Max Welling
Jakub M. Tomczak
AAML
DRL
33
10
0
10 Mar 2021
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