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Properties from Mechanisms: An Equivariance Perspective on Identifiable
  Representation Learning

Properties from Mechanisms: An Equivariance Perspective on Identifiable Representation Learning

29 October 2021
Kartik Ahuja
Jason S. Hartford
Yoshua Bengio
ArXivPDFHTML

Papers citing "Properties from Mechanisms: An Equivariance Perspective on Identifiable Representation Learning"

12 / 12 papers shown
Title
What is causal about causal models and representations?
What is causal about causal models and representations?
Frederik Hytting Jørgensen
Luigi Gresele
S. Weichwald
CML
105
0
0
31 Jan 2025
Linear causal disentanglement via higher-order cumulants
Linear causal disentanglement via higher-order cumulants
Paula Leyes Carreno
Chiara Meroni
A. Seigal
CML
36
0
0
05 Jul 2024
Sparsity regularization via tree-structured environments for
  disentangled representations
Sparsity regularization via tree-structured environments for disentangled representations
Elliot Layne
Jason S. Hartford
Sébastien Lachapelle
Mathieu Blanchette
Dhanya Sridhar
OOD
CML
33
0
0
30 May 2024
Nonparametric Identifiability of Causal Representations from Unknown
  Interventions
Nonparametric Identifiability of Causal Representations from Unknown Interventions
Julius von Kügelgen
M. Besserve
Wendong Liang
Luigi Gresele
Armin Kekić
Elias Bareinboim
David M. Blei
Bernhard Schölkopf
CML
18
56
0
01 Jun 2023
Equivariant Representation Learning in the Presence of Stabilizers
Equivariant Representation Learning in the Presence of Stabilizers
Luis Armando
∗. GiovanniLucaMarchetti
Danica Kragic
D. Jarnikov
Mike Holenderski
29
0
0
12 Jan 2023
Linear Causal Disentanglement via Interventions
Linear Causal Disentanglement via Interventions
C. Squires
A. Seigal
Salil Bhate
Caroline Uhler
CML
29
66
0
29 Nov 2022
Weakly Supervised Representation Learning with Sparse Perturbations
Weakly Supervised Representation Learning with Sparse Perturbations
Kartik Ahuja
Jason S. Hartford
Yoshua Bengio
SSL
35
58
0
02 Jun 2022
Identifiable Deep Generative Models via Sparse Decoding
Identifiable Deep Generative Models via Sparse Decoding
Gemma E. Moran
Dhanya Sridhar
Yixin Wang
David M. Blei
BDL
28
44
0
20 Oct 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
M. Bronstein
Joan Bruna
Taco S. Cohen
Petar Velivcković
GNN
174
1,104
0
27 Apr 2021
Contrastive Learning Inverts the Data Generating Process
Contrastive Learning Inverts the Data Generating Process
Roland S. Zimmermann
Yash Sharma
Steffen Schneider
Matthias Bethge
Wieland Brendel
SSL
238
207
0
17 Feb 2021
Weakly-Supervised Disentanglement Without Compromises
Weakly-Supervised Disentanglement Without Compromises
Francesco Locatello
Ben Poole
Gunnar Rätsch
Bernhard Schölkopf
Olivier Bachem
Michael Tschannen
CoGe
OOD
DRL
178
313
0
07 Feb 2020
A Style-Based Generator Architecture for Generative Adversarial Networks
A Style-Based Generator Architecture for Generative Adversarial Networks
Tero Karras
S. Laine
Timo Aila
279
10,348
0
12 Dec 2018
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