Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis

4 June 2022

Papers citing "Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis"

35 / 35 papers shown

Title
Characterization and Learning of Causal Graphs from Hard Interventions Zihan Zhou Muhammad Qasim Elahi Murat Kocaoglu CML 69 0 0 02 May 2025
Multi-Domain Causal Discovery in Bijective Causal Models Kasra Jalaldoust Saber Salehkaleybar Negar Kiyavash CML 64 0 0 30 Apr 2025
DGFamba: Learning Flow Factorized State Space for Visual Domain Generalization Qi Bi Jingjun Yi Hao Zheng Haolan Zhan Wei Ji Yawen Huang Yuexiang Li OOD 28 1 0 10 Apr 2025
Causally Aligned Curriculum Learning Mingxuan Li Junzhe Zhang Elias Bareinboim CML 56 3 0 21 Mar 2025
Falsification of Unconfoundedness by Testing Independence of Causal Mechanisms R. Karlsson Jesse H. Krijthe CML 47 0 0 10 Feb 2025
SpaceTime: Causal Discovery from Non-Stationary Time Series Sarah Mameche Lénaïg Cornanguer Urmi Ninad Jilles Vreeken CML AI4TS 33 0 0 20 Jan 2025
Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Kai Helli David Schnurr Noah Hollmann Samuel G. Müller Frank Hutter OOD 31 4 0 15 Nov 2024
Detecting and Measuring Confounding Using Causal Mechanism Shifts Abbavaram Gowtham Reddy Vineeth N Balasubramanian CML 15 1 0 26 Sep 2024
DGMamba: Domain Generalization via Generalized State Space Model Shaocong Long Qianyu Zhou Xiangtai Li Xuequan Lu Chenhao Ying Yuan Luo Lizhuang Ma Shuicheng Yan 47 9 0 11 Apr 2024
A Sparsity Principle for Partially Observable Causal Representation Learning Danru Xu Dingling Yao Sébastien Lachapelle Perouz Taslakian Julius von Kügelgen Francesco Locatello Sara Magliacane CML 25 13 0 13 Mar 2024
Implicit Causal Representation Learning via Switchable Mechanisms Shayan Shirahmad Gale Bagi Zahra Gharaee Oliver Schulte Mark Crowley CML 42 0 0 16 Feb 2024
Learning Unknown Intervention Targets in Structural Causal Models from Heterogeneous Data Yuqin Yang Saber Salehkaleybar Negar Kiyavash CML 8 1 0 11 Dec 2023
An Interventional Perspective on Identifiability in Gaussian LTI Systems with Independent Component Analysis Goutham Rajendran Patrik Reizinger Wieland Brendel Pradeep Ravikumar CML 18 8 0 29 Nov 2023
Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions Simon Bing Urmi Ninad Jonas Wahl Jakob Runge CML 8 5 0 05 Nov 2023
Extracting the Multiscale Causal Backbone of Brain Dynamics Gabriele DÁcunto Francesco Bonchi G. D. F. Morales Giovanni Petri 9 0 0 31 Oct 2023
Deep Backtracking Counterfactuals for Causally Compliant Explanations Klaus-Rudolf Kladny Julius von Kügelgen Bernhard Schölkopf Michael Muehlebach BDL 24 4 0 11 Oct 2023
Rethinking Domain Generalization: Discriminability and Generalizability Shaocong Long Qianyu Zhou Chenhao Ying Lizhuang Ma Yuan Luo OOD AI4CE 13 12 0 28 Sep 2023
Exploiting Causality Signals in Medical Images: A Pilot Study with Empirical Results Gianluca Carloni Sara Colantonio 16 8 0 19 Sep 2023
Causal Reinforcement Learning: A Survey Zhi-Hong Deng Jing Jiang Guodong Long Chen Zhang CML LRM 34 13 0 04 Jul 2023
iSCAN: Identifying Causal Mechanism Shifts among Nonlinear Additive Noise Models Tianyu Chen Kevin Bello Bryon Aragam Pradeep Ravikumar CML 17 1 0 30 Jun 2023
Leveraging Task Structures for Improved Identifiability in Neural Network Representations Wenlin Chen Julien Horwood Juyeon Heo José Miguel Hernández-Lobato CML 14 1 0 26 Jun 2023
Learning nonparametric latent causal graphs with unknown interventions Yibo Jiang Bryon Aragam CML 11 24 0 05 Jun 2023
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 8 56 0 01 Jun 2023
Causal Component Analysis Wendong Liang Armin Kekić Julius von Kügelgen Simon Buchholz M. Besserve Luigi Gresele Bernhard Schölkopf CML 16 36 0 26 May 2023
Out-of-Variable Generalization for Discriminative Models Siyuan Guo J. Wildberger Bernhard Schölkopf OOD CML 9 2 0 16 Apr 2023
MetaPhysiCa: OOD Robustness in Physics-informed Machine Learning S Chandra Mouli M. A. Alam Bruno Ribeiro OOD 10 4 0 06 Mar 2023
On the Interventional Kullback-Leibler Divergence J. Wildberger Siyuan Guo Arnab Bhattacharyya Bernhard Schölkopf OOD CML 13 6 0 10 Feb 2023
Score-based Causal Representation Learning with Interventions Burak Varici Emre Acartürk Karthikeyan Shanmugam Abhishek Kumar A. Tajer CML 19 38 0 19 Jan 2023
Learning Multiscale Non-stationary Causal Structures Gabriele DÁcunto G. D. F. Morales P. Bajardi Francesco Bonchi CML AI4TS 30 3 0 31 Aug 2022
Active Bayesian Causal Inference Christian Toth Lars Lorch Christian Knoll Andreas Krause Franz Pernkopf Robert Peharz Julius von Kügelgen 32 26 0 04 Jun 2022
Which Invariance Should We Transfer? A Causal Minimax Learning Approach Mingzhou Liu Xiangyu Zheng Xinwei Sun Fang Fang Yizhou Wang OOD 8 2 0 05 Jul 2021
Does Invariant Risk Minimization Capture Invariance? Pritish Kamath Akilesh Tangella Danica J. Sutherland Nathan Srebro OOD 185 125 0 04 Jan 2021
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
Causal Network Learning from Multiple Interventions of Unknown Manipulated Targets Y. He Z. Geng CML 29 13 0 27 Oct 2016
Causal Inference in the Presence of Latent Variables and Selection Bias Peter Spirtes Christopher Meek Thomas S. Richardson CML 133 434 0 20 Feb 2013