NeurIPS 2024PastCausality

NeurIPS 2024 Causal Representation Learning Workshop

CRL@NeurIPS 2024

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Submission deadline: Oct 2, 2024, 23:59 UTC
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Submission portal: OpenReview
Notes: Topics were auto-suggested and may be imprecise — edits welcome.

Accepted papers (37)

Fetched from OpenReview (v2) on 2026-06-10.

A Causality-Inspired Spatial-Temporal Return Decomposition Approach for Multi-Agent Reinforcement Learning
Yudi Zhang, Yali Du, Biwei Huang, Meng Fang, Mykola Pechenizkiy · PDF
A Novel Application of SCMs to Time Series Counterfactual Estimation in the Pharmaceutical Industry
Tomas Garriga, Gerard Sanz, Eduard Serrahima de Cambra, Axel Brando · PDF
A Shadow Variable Approach to Causal Decision Making with One-sided Feedback
Jianing Chu, Shu Yang, Wenbin Lu, PULAK GHOSH · PDF
Beyond Causal Discovery for Astronomy: Learning Meaningful Representations with Independent Component Analysis
Zehao Jin, Mario Pasquato, Benjamin L. Davis, Andrea Maccio, Yashar Hezaveh · PDF
Causal Discovery in Linear Models with Unobserved Variables and Measurement Error
Yuqin Yang, Mohamed S Nafea, Negar Kiyavash, Kun Zhang, AmirEmad Ghassami · PDF
Causal Inference under Differential Privacy: Challenges and Mitigation Strategies
Amirhossein Farzam, Guillermo Sapiro · PDF
Causal Order Discovery based on Monotonic SCMs
Ali Izadi, Martin Ester · PDF
Causal Representation Learning for Cross-Patient Seizure Classification
Chunyuan Zheng, Yan Lyu, Taojun Hu, Xiaoxin Liu, Xiao-Hua Zhou · PDF
Causal Retrieval with Semantic Consideration
Hyunseo Shin, Wonseok Hwang · PDF
CSRec: Rethinking Sequential Recommendation from A Causal Perspective.
Xiaoyu Liu, Jiaxin Yuan, Yuhang Zhou, Jingling Li, Furong Huang, Wei Ai · PDF
DAG-aware Transformer for Causal Effect Estimation
Manqing Liu, David Remy Bellamy, Andrew Beam · PDF
Deep Learning Methods for the Noniterative Conditional Expectation G-Formula for Causal Inference from Complex Observational Data
Sophia M Rein, Jing Li, Miguel Hernan, Andrew Beam · PDF
Differentiable Causal Discovery for Latent Hierarchical Causal Models
Parjanya Prajakta Prashant, Ignavier Ng, Kun Zhang, Biwei Huang · PDF
Estimating Treatment Effect across Heterogeneous Data Sources: An Instrumental Variable Approach
Haotian Wang, Haoxuan Li, Wenjing Yang, Hao Zou, Wanrong Huang, Kun Kuang · PDF
From Text to Treatment Effects: A Meta-Learning Approach to Handling Text-Based Confounding
Henri Arno, Paloma Rabaey, Thomas Demeester · PDF
General Causal Imputation via Synthetic Interventions
Marco Jiralerspong, Thomas Jiralerspong, Vedant Shah, Dhanya Sridhar, Gauthier Gidel · PDF
Improving Causal Transplant Outcomes through Dynamic Organ Offer Estimation
Alessandro Marchese, Hans de Ferrante, Jeroen Berrevoets, Sam Verboven · PDF
Interaction Asymmetry: A General Principle for Learning Composable Abstractions
Jack Brady, Julius von Kügelgen, Sebastien Lachapelle, Simon Buchholz, Wieland Brendel · PDF
Learning Joint Interventional Effects from Single-Variable Interventions in Additive Models
Armin Kekić, Sergio Hernan Garrido Mejia, Bernhard Schölkopf · PDF
Leveraging a Simulator for Learning Causal Representations for CATE from Post-Treatment Covariates
Lokesh Nagalapatti, Pranava Singhal, Avishek Ghosh, Sunita Sarawagi · PDF
LLMs as Emotion Analyzers for Causal Models: Partial Identification with Fuzzy Interval Data
Huidi Ma, Wendao Xue, Yifan Yu · PDF
MACCA: Offline Multi-agent Reinforcement Learning with Causal Credit Assignment
Ziyan Wang, Yali Du, Yudi Zhang, Meng Fang, Biwei Huang · PDF
On Domain Generalization Datasets as Proxy Benchmarks for Causal Representation Learning
Olawale Elijah Salaudeen, Nicole Chiou, Sanmi Koyejo · PDF
On the role of prognostic factors and effect modifiers in structural causal models
Rianne M. Schouten · PDF
Pilot Analysis for: Learning to Encode Multi-level Dynamics in Effect Heterogeneity Estimation
Fucheng Warren Zhu, Connor Thomas Jerzak, Adel Daoud · PDF
Robust Domain Generalisation with Causal Invariant Bayesian Neural Networks
Gael Gendron, Michael Witbrock, Gillian Dobbie · PDF
Robust Multi-view Co-expression Network Inference
Teodora Pandeva, Martijs Johannes Jonker, Leendert Hamoen, Joris Mooij, Patrick Forré · PDF
Score-Based Interaction Testing in Pairwise Experiments
Jana Osea, Zuheng Xu, Cian Eastwood, Jason Hartford · PDF
Since Faithfulness Fails: The Performance Limits of Neural Causal Discovery
Mateusz Olko, Mateusz Gajewski, Joanna Wojciechowska, Łukasz Kuciński, Mikołaj Morzy, Piotr Sankowski, Piotr Miłoś · PDF
Spectral Representation for Causal Estimation with Hidden Confounders
Tongzheng Ren, Haotian Sun, Antoine Moulin, Arthur Gretton, Bo Dai · PDF
Systems with Switching Causal Relations: A Meta-Causal Perspective
Moritz Willig, Tim Tobiasch, Florian Peter Busch, Jonas Seng, Devendra Singh Dhami, Kristian Kersting · PDF
Teaching Invariance Using Privileged Mediation Information
Dylan Zapzalka, Maggie Makar · PDF
Uncertainty-Aware Optimal Treatment Selection for Clinical Time Series
Thomas Schwarz, Cecilia Casolo, Niki Kilbertus · PDF
Uncovering Latent Causal Structures from Spatiotemporal Data
Kun Wang, Sumanth Varambally, Duncan Watson-Parris, Yian Ma, Rose Yu · PDF
Unifying Causal Representation Learning with the Invariance Principle
Dingling Yao, Dario Rancati, Riccardo Cadei, Marco Fumero, Francesco Locatello · PDF
Unsupervised Causal Abstraction
Yuchen Zhu, Sergio Hernan Garrido Mejia, Bernhard Schölkopf, Michel Besserve · PDF
Zero-Shot Learning of Causal Models
Divyat Mahajan, Jannes Gladrow, Agrin Hilmkil, Cheng Zhang, Meyer Scetbon · PDF

Accepted papers (37)

☆A Causality-Inspired Spatial-Temporal Return Decomposition Approach for Multi-Agent Reinforcement Learning

☆A Novel Application of SCMs to Time Series Counterfactual Estimation in the Pharmaceutical Industry

☆A Shadow Variable Approach to Causal Decision Making with One-sided Feedback

☆Beyond Causal Discovery for Astronomy: Learning Meaningful Representations with Independent Component Analysis

☆Causal Discovery in Linear Models with Unobserved Variables and Measurement Error

☆Causal Inference under Differential Privacy: Challenges and Mitigation Strategies

☆Causal Order Discovery based on Monotonic SCMs

☆Causal Representation Learning for Cross-Patient Seizure Classification

☆Causal Retrieval with Semantic Consideration

☆CSRec: Rethinking Sequential Recommendation from A Causal Perspective.

☆DAG-aware Transformer for Causal Effect Estimation

☆Deep Learning Methods for the Noniterative Conditional Expectation G-Formula for Causal Inference from Complex Observational Data

☆Differentiable Causal Discovery for Latent Hierarchical Causal Models

☆Estimating Treatment Effect across Heterogeneous Data Sources: An Instrumental Variable Approach

☆From Text to Treatment Effects: A Meta-Learning Approach to Handling Text-Based Confounding

☆General Causal Imputation via Synthetic Interventions

☆Improving Causal Transplant Outcomes through Dynamic Organ Offer Estimation

☆Interaction Asymmetry: A General Principle for Learning Composable Abstractions

☆Learning Joint Interventional Effects from Single-Variable Interventions in Additive Models

☆Leveraging a Simulator for Learning Causal Representations for CATE from Post-Treatment Covariates

☆LLMs as Emotion Analyzers for Causal Models: Partial Identification with Fuzzy Interval Data

☆MACCA: Offline Multi-agent Reinforcement Learning with Causal Credit Assignment

☆On Domain Generalization Datasets as Proxy Benchmarks for Causal Representation Learning

☆On the role of prognostic factors and effect modifiers in structural causal models

☆Pilot Analysis for: Learning to Encode Multi-level Dynamics in Effect Heterogeneity Estimation

☆Robust Domain Generalisation with Causal Invariant Bayesian Neural Networks

☆Robust Multi-view Co-expression Network Inference

☆Score-Based Interaction Testing in Pairwise Experiments

☆Since Faithfulness Fails: The Performance Limits of Neural Causal Discovery

☆Spectral Representation for Causal Estimation with Hidden Confounders

☆Systems with Switching Causal Relations: A Meta-Causal Perspective

☆Teaching Invariance Using Privileged Mediation Information

☆Uncertainty-Aware Optimal Treatment Selection for Clinical Time Series

☆Uncovering Latent Causal Structures from Spatiotemporal Data

☆Unifying Causal Representation Learning with the Invariance Principle

☆Unsupervised Causal Abstraction

☆Zero-Shot Learning of Causal Models

A Causality-Inspired Spatial-Temporal Return Decomposition Approach for Multi-Agent Reinforcement Learning

A Novel Application of SCMs to Time Series Counterfactual Estimation in the Pharmaceutical Industry

A Shadow Variable Approach to Causal Decision Making with One-sided Feedback

Beyond Causal Discovery for Astronomy: Learning Meaningful Representations with Independent Component Analysis

Causal Discovery in Linear Models with Unobserved Variables and Measurement Error

Causal Inference under Differential Privacy: Challenges and Mitigation Strategies

Causal Order Discovery based on Monotonic SCMs

Causal Representation Learning for Cross-Patient Seizure Classification

Causal Retrieval with Semantic Consideration

CSRec: Rethinking Sequential Recommendation from A Causal Perspective.

DAG-aware Transformer for Causal Effect Estimation

Deep Learning Methods for the Noniterative Conditional Expectation G-Formula for Causal Inference from Complex Observational Data

Differentiable Causal Discovery for Latent Hierarchical Causal Models

Estimating Treatment Effect across Heterogeneous Data Sources: An Instrumental Variable Approach

From Text to Treatment Effects: A Meta-Learning Approach to Handling Text-Based Confounding

General Causal Imputation via Synthetic Interventions

Improving Causal Transplant Outcomes through Dynamic Organ Offer Estimation

Interaction Asymmetry: A General Principle for Learning Composable Abstractions

Learning Joint Interventional Effects from Single-Variable Interventions in Additive Models

Leveraging a Simulator for Learning Causal Representations for CATE from Post-Treatment Covariates

LLMs as Emotion Analyzers for Causal Models: Partial Identification with Fuzzy Interval Data

MACCA: Offline Multi-agent Reinforcement Learning with Causal Credit Assignment

On Domain Generalization Datasets as Proxy Benchmarks for Causal Representation Learning

On the role of prognostic factors and effect modifiers in structural causal models

Pilot Analysis for: Learning to Encode Multi-level Dynamics in Effect Heterogeneity Estimation

Robust Domain Generalisation with Causal Invariant Bayesian Neural Networks

Robust Multi-view Co-expression Network Inference

Score-Based Interaction Testing in Pairwise Experiments

Since Faithfulness Fails: The Performance Limits of Neural Causal Discovery

Spectral Representation for Causal Estimation with Hidden Confounders

Systems with Switching Causal Relations: A Meta-Causal Perspective

Teaching Invariance Using Privileged Mediation Information

Uncertainty-Aware Optimal Treatment Selection for Clinical Time Series

Uncovering Latent Causal Structures from Spatiotemporal Data

Unifying Causal Representation Learning with the Invariance Principle

Unsupervised Causal Abstraction

Zero-Shot Learning of Causal Models