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Weakly supervised causal representation learning

Weakly supervised causal representation learning

30 March 2022
Johann Brehmer
P. D. Haan
Phillip Lippe
Taco S. Cohen
    OOD
    CML
ArXivPDFHTML

Papers citing "Weakly supervised causal representation learning"

13 / 13 papers shown
Title
Q-function Decomposition with Intervention Semantics with Factored Action Spaces
Q-function Decomposition with Intervention Semantics with Factored Action Spaces
Junkyu Lee
Tian Gao
Elliot Nelson
Miao Liu
D. Bhattacharjya
Songtao Lu
OffRL
45
0
0
30 Apr 2025
I Predict Therefore I Am: Is Next Token Prediction Enough to Learn Human-Interpretable Concepts from Data?
I Predict Therefore I Am: Is Next Token Prediction Enough to Learn Human-Interpretable Concepts from Data?
Yuhang Liu
Dong Gong
Erdun Gao
Zhen Zhang
Biwei Huang
Mingming Gong
Anton van den Hengel
Javen Qinfeng Shi
J. Shi
69
0
0
12 Mar 2025
Sanity Checking Causal Representation Learning on a Simple Real-World System
Sanity Checking Causal Representation Learning on a Simple Real-World System
Juan L. Gamella
Simon Bing
Jakob Runge
CML
47
0
0
27 Feb 2025
What is causal about causal models and representations?
What is causal about causal models and representations?
Frederik Hytting Jørgensen
Luigi Gresele
S. Weichwald
CML
99
0
0
31 Jan 2025
A Complexity-Based Theory of Compositionality
A Complexity-Based Theory of Compositionality
Eric Elmoznino
Thomas Jiralerspong
Yoshua Bengio
Guillaume Lajoie
CoGe
56
3
0
18 Oct 2024
Counterfactual Generative Modeling with Variational Causal Inference
Counterfactual Generative Modeling with Variational Causal Inference
Yulun Wu
Louie McConnell
Claudia Iriondo
CML
BDL
20
0
0
16 Oct 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
20
0
0
30 May 2024
Causal Diffusion Autoencoders: Toward Counterfactual Generation via
  Diffusion Probabilistic Models
Causal Diffusion Autoencoders: Toward Counterfactual Generation via Diffusion Probabilistic Models
Aneesh Komanduri
Chengli Zhao
Feng Chen
Xintao Wu
CML
DiffM
28
4
0
27 Apr 2024
Towards a Unified Framework of Contrastive Learning for Disentangled
  Representations
Towards a Unified Framework of Contrastive Learning for Disentangled Representations
Stefan Matthes
Zhiwei Han
Hao Shen
14
4
0
08 Nov 2023
Conditionally Invariant Representation Learning for Disentangling
  Cellular Heterogeneity
Conditionally Invariant Representation Learning for Disentangling Cellular Heterogeneity
H. Aliee
Ferdinand Kapl
Soroor Hediyeh-zadeh
Fabian J. Theis
CML
13
6
0
02 Jul 2023
Towards Characterizing Domain Counterfactuals For Invertible Latent
  Causal Models
Towards Characterizing Domain Counterfactuals For Invertible Latent Causal Models
Zeyu Zhou
Ruqi Bai
Sean Kulinski
Murat Kocaoglu
David I. Inouye
CML
19
1
0
20 Jun 2023
Neuro-Causal Factor Analysis
Neuro-Causal Factor Analysis
Alex Markham
Ming-Yu Liu
Bryon Aragam
Liam Solus
CML
13
3
0
31 May 2023
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
171
311
0
07 Feb 2020
1