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A Causal Ordering Prior for Unsupervised Representation Learning

A Causal Ordering Prior for Unsupervised Representation Learning

11 July 2023
Avinash Kori
Pedro Sanchez
Konstantinos Vilouras
Ben Glocker
Sotirios A. Tsaftaris
    BDLSSLCML
ArXiv (abs)PDFHTML

Papers citing "A Causal Ordering Prior for Unsupervised Representation Learning"

14 / 14 papers shown
Title
Identifiability of deep generative models without auxiliary information
Identifiability of deep generative models without auxiliary information
Bohdan Kivva
Goutham Rajendran
Pradeep Ravikumar
Bryon Aragam
DRL
91
52
0
20 Jun 2022
Weakly supervised causal representation learning
Weakly supervised causal representation learning
Johann Brehmer
P. D. Haan
Phillip Lippe
Taco S. Cohen
OODCML
88
131
0
30 Mar 2022
Score matching enables causal discovery of nonlinear additive noise
  models
Score matching enables causal discovery of nonlinear additive noise models
Paul Rolland
Volkan Cevher
Matthäus Kleindessner
Chris Russel
Bernhard Schölkopf
Dominik Janzing
Francesco Locatello
CML
90
90
0
08 Mar 2022
Learning Disentangled Representations in the Imaging Domain
Learning Disentangled Representations in the Imaging Domain
Xiao Liu
Pedro Sanchez
Spyridon Thermos
Alison Q. OÑeil
Sotirios A. Tsaftaris
OODDRL
102
72
0
26 Aug 2021
I Don't Need u: Identifiable Non-Linear ICA Without Side Information
I Don't Need u: Identifiable Non-Linear ICA Without Side Information
M. Willetts
Brooks Paige
CMLOOD
46
25
0
09 Jun 2021
Self-Supervised Learning with Data Augmentations Provably Isolates
  Content from Style
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style
Julius von Kügelgen
Yash Sharma
Luigi Gresele
Wieland Brendel
Bernhard Schölkopf
M. Besserve
Francesco Locatello
99
317
0
08 Jun 2021
ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on
  Nonlinear ICA
ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on Nonlinear ICA
Ilyes Khemakhem
R. Monti
Diederik P. Kingma
Aapo Hyvarinen
CML
81
114
0
26 Feb 2020
Weakly-Supervised Disentanglement Without Compromises
Weakly-Supervised Disentanglement Without Compromises
Francesco Locatello
Ben Poole
Gunnar Rätsch
Bernhard Schölkopf
Olivier Bachem
Michael Tschannen
CoGeOODDRL
242
320
0
07 Feb 2020
Disentangling by Factorising
Disentangling by Factorising
Hyunjik Kim
A. Mnih
CoGeOOD
64
1,356
0
16 Feb 2018
Variational Deep Embedding: An Unsupervised and Generative Approach to
  Clustering
Variational Deep Embedding: An Unsupervised and Generative Approach to Clustering
Zhuxi Jiang
Yin Zheng
Huachun Tan
Bangsheng Tang
Hanning Zhou
BDLDRL
82
732
0
16 Nov 2016
InfoGAN: Interpretable Representation Learning by Information Maximizing
  Generative Adversarial Nets
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets
Xi Chen
Yan Duan
Rein Houthooft
John Schulman
Ilya Sutskever
Pieter Abbeel
GAN
159
4,238
0
12 Jun 2016
Auto-Encoding Variational Bayes
Auto-Encoding Variational Bayes
Diederik P. Kingma
Max Welling
BDL
455
16,923
0
20 Dec 2013
Causal Discovery with Continuous Additive Noise Models
Causal Discovery with Continuous Additive Noise Models
Jonas Peters
Joris Mooij
Dominik Janzing
Bernhard Schölkopf
CML
106
573
0
26 Sep 2013
Representation Learning: A Review and New Perspectives
Representation Learning: A Review and New Perspectives
Yoshua Bengio
Aaron Courville
Pascal Vincent
OODSSL
274
12,458
0
24 Jun 2012
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