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Implicit Causal Representation Learning via Switchable Mechanisms

Implicit Causal Representation Learning via Switchable Mechanisms

16 February 2024
Shayan Shirahmad Gale Bagi
Zahra Gharaee
Oliver Schulte
Mark Crowley
    CML
ArXivPDFHTML

Papers citing "Implicit Causal Representation Learning via Switchable Mechanisms"

13 / 13 papers shown
Title
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
116
64
0
01 Jun 2023
Generative Causal Representation Learning for Out-of-Distribution Motion
  Forecasting
Generative Causal Representation Learning for Out-of-Distribution Motion Forecasting
Shayan Shirahmad Gale Bagi
Zahra Gharaee
Oliver Schulte
Mark Crowley
OODD
OOD
70
13
0
17 Feb 2023
On the Identifiability of Nonlinear ICA: Sparsity and Beyond
On the Identifiability of Nonlinear ICA: Sparsity and Beyond
Yujia Zheng
Ignavier Ng
Kun Zhang
CML
47
63
0
15 Jun 2022
Causal Discovery in Heterogeneous Environments Under the Sparse
  Mechanism Shift Hypothesis
Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis
Ronan Perry
Julius von Kügelgen
Bernhard Schölkopf
91
50
0
04 Jun 2022
Weakly supervised causal representation learning
Weakly supervised causal representation learning
Johann Brehmer
P. D. Haan
Phillip Lippe
Taco S. Cohen
OOD
CML
82
130
0
30 Mar 2022
Differentiable DAG Sampling
Differentiable DAG Sampling
Bertrand Charpentier
Simon Kibler
Stephan Günnemann
78
42
0
16 Mar 2022
Efficient Neural Causal Discovery without Acyclicity Constraints
Efficient Neural Causal Discovery without Acyclicity Constraints
Phillip Lippe
Taco S. Cohen
E. Gavves
CML
52
72
0
22 Jul 2021
Disentanglement via Mechanism Sparsity Regularization: A New Principle
  for Nonlinear ICA
Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA
Sébastien Lachapelle
Pau Rodríguez López
Yash Sharma
Katie Everett
Rémi Le Priol
Alexandre Lacoste
Simon Lacoste-Julien
CML
OOD
87
139
0
21 Jul 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
97
314
0
08 Jun 2021
Learning causal representations for robust domain adaptation
Learning causal representations for robust domain adaptation
shuai Yang
Kui Yu
Fuyuan Cao
Lin Liu
Hongya Wang
Jiuyong Li
OOD
CML
TTA
58
44
0
12 Nov 2020
Rescaling Egocentric Vision
Rescaling Egocentric Vision
Dima Damen
Hazel Doughty
G. Farinella
Antonino Furnari
Evangelos Kazakos
...
Davide Moltisanti
Jonathan Munro
Toby Perrett
Will Price
Michael Wray
EgoV
72
460
0
23 Jun 2020
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
237
317
0
07 Feb 2020
DAG-GNN: DAG Structure Learning with Graph Neural Networks
DAG-GNN: DAG Structure Learning with Graph Neural Networks
Yue Yu
Jie Chen
Tian Gao
Mo Yu
BDL
CML
GNN
78
487
0
22 Apr 2019
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