Consistent End-to-End Estimation for Counterfactual Fairness

Yuchen Ma, Valentyn Melnychuk, Dennis Frauen, Stefan Feuerriegel; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:1-49

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Retrospective Counterfactual Prediction by Conditioning on the Factual Outcome: A Cross-World Approach

Juraj Bodik; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:50-83

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Local Markov Equivalence for PC-style Local Causal Discovery and Identification of Controlled Direct Effects

Timothée Loranchet, Charles K. Assaad; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:84-118

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Disentangling Dynamical Systems: Causal Representation Learning Meets Local Sparse Attention

Markus W. Baumgartner, Anson Lei, Joe Watson, Ingmar Posner; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:119-165

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A fine-grained look at causal effects in causal spaces

Junhyung Park, Yuqing Zhou; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:166-195

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Understanding Task Representations in Neural Networks via Bayesian Ablation

Andrew Joohun Nam, Declan Iain Campbell, Thomas L. Griffiths, Jonathan D. Cohen, Sarah-Jane Leslie; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:196-221

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Valid Inference for Treatment Effects under Multimodal Confounding

Martin Spindler, Philipp Bach, Victor Chernozhukov, Sven Klaassen, Jan Teichert-Kluge, Suhas Vijaykumar; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:222-247

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Causal-ICM: A Data Fusion Framework For Heterogeneous Treatment Effect Estimation With Multi-Task Gaussian Processes

Evangelos Dimitriou, Edwin Fong, Jens Magelund Tarp, Karla DiazOrdaz, Brieuc Lehmann; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:248-276

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DAG Learning from Zero-Inflated Count Data Using Continuous Optimization

Noriaki Sato, Marco Scutari, Shuichi Kawano, Rui Yamaguchi, Seiya Imoto; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:277-296

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A novel hybrid approach for positive-valued DAG learning

Yao Zhao; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:297-323

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Bayesian Hierarchical Invariant Prediction

Francisco Madaleno, Pernille Julie Viuff Sand, Francisco C. Pereira, Sergio Hernan Garrido Mejia; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:324-352

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Automatic debiased machine learning and sensitivity analysis for sample selection models

Jakob Bjelac, Victor Chernozhukov, Phil-Adrian Klotz, Jannis Kueck, Theresa M. A. Schmitz; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:353-392

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Retrieving Classes of Causal Orders with Inconsistent Knowledge Bases

Federico Baldo, Simon Ferreira, Charles K. Assaad; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:393-422

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Cross-Sectional Conditional Independence in Stationary Time Series: Graphical Equivalence and Completeness of Collider Separation

Hubert Marek Drazkowski; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:423-478

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Improving Generative Methods for Causal Evaluation via Simulation-Based Inference

Pracheta Amaranath, Vinitra Muralikrishnan, Amit Sharma, David Jensen; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:479-546

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Learning a Spatial Partitioning and its Causal Relations from Temporal Data

Philippe Brouillard, Sebastien Lachapelle, Julia Kaltenborn, Yaniv Gurwicz, Dhanya Sridhar, Alexandre Drouin, Peer Nowack, Jakob Runge, David Rolnick; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:547-592

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Evaluating and Learning Robust Bandit Policies Under Uncertain Causal Mechanisms

Katherine Avery, Chinmay Pendse, David Jensen; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:593-626

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Causal Importance for Physics-Informed Machine Learning

Daniel Fiifi Tawia Hagan, Thomas Mortier, Cas Decancq, Diego G. Miralles; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:627-655

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Learning and Testing Exposure Mappings of Interference using Graph Convolutional Autoencoders

Martin Huber, Jannis Kueck, Mara Mattes; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:656-675

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Estimating Joint Interventional Distributions from Marginal Interventional Data

Sergio Hernan Garrido Mejia, Elke Kirschbaum, Armin Kekić, Bernhard Schölkopf, Atalanti A. Mastakouri; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:676-698

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Variance reduction combining pre-experiment and in-experiment data

Zhexiao Lin, Pablo Crespo; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:699-717

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Estimating PATE under positivity violations: SBART+SPL for high-dimensional covariates

Lennard Maßmann; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:718-756

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Unveiling Causal Calibration: How LLM Scale Influences Statistical Information Interpolation

Markus Englberger, Devendra Singh Dhami; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:757-775

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Smoothing the Landscape: Causal Structure Learning via Diffusion Denoising Objectives

Hao Zhu, Di Zhou, Donna Slonim; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:776-822

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Learning control variables and instruments for causal analysis in observational data

Nicolas Apfel, Martin Huber, Jannis Kueck, Julia Hatamyar; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:823-860

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Flow IV: Counterfactual Inference In Nonseparable Outcome Models Using Instrumental Variables

Marc Braun, Jose Peña, Adel Daoud; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:861-886

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Composite Graphical Causal Models for Inference on Heterogeneous-Indexed Data

Arne De Temmerman, Mathias Verbeke; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:887-910

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A Comprehensive Collection of Vignettes for Actual Causation

Christian Odenwald; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:911-931

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Abstractions in Causal Models and Game Structures

Sylvia S. Kerkhove, Natasha Alechina, Mehdi Dastani; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:932-948

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A causal machine learning framework for pharmacovigilance signal detection in electronic health records: Drug-induced acute kidney injury

Stella Dimitsaki, Corinne Isnard Bagnis, Pantelis Natsiavas, Marie-Christine Jaulent; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:949-1029

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Causal Articulation Theory (CAT): Articulating Static and Temporal Causal Models Beyond LLM Rationalizations

Matej Zečević, Devendra Singh Dhami, Kristian Kersting; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:1030-1067

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Cost-Aware Optimized Front-Door Experimental Design

Leopold Mareis, Mathias Drton; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:1068-1096

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Bivariate Causal Discovery Using Rate-Distortion MDL: An Information Dimension Approach

Tiago Brogueira, Mario A. T. Figueiredo; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:1097-1118

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Information-theoretic signatures of causality in Bayesian networks and hypergraphs

Sung En Chiang, Zhaolu Liu, Robert Peach, Mauricio Barahona; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:1119-1139

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Causal Foundations of Collective Agency

Frederik Hytting Jørgensen, Sebastian Weichwald, Lewis Hammond; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:1140-1170

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Nonparametric Greedy Equivalence Search with Prior-Fitted Networks

Mateusz Gajewski, Mateusz Olko; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:1171-1197

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The Generalised Kernel Covariance Measure

Luca Bergen, Dino Sejdinovic, Vanessa Didelez; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:1198-1220

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Domain Faithfulness through Counterfactually Robust Learning

Ananth Balashankar, Ankit Bhardwaj, Neelabh Madan, Thomas Wies, Lakshmi Subramanian; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:1221-1249

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Beware of Hinges in Proximal Variables Regression: Adjusting for Colliding-Mediators with Nuisance PV

Hubert Marek Drazkowski; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:1250-1292

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IV Co-Scientist: Multi-Agent LLM Framework for Causal Instrumental Variable Discovery

Ivaxi Sheth, Zhijing Jin, Bryan Wilder, Dominik Janzing, Mario Fritz; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:1293-1317

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Coarsening Causal DAG Models

Francisco Madaleno, Pratik Misra, Alex Markham; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:1318-1344

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Debiased Machine Learning for Conformal Prediction of Counterfactual Outcomes Under Runtime Confounding

Keith Barnatchez, Kevin P. Josey, Rachel C. Nethery, Giovanni Parmigiani; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:1345-1379

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Estimation and Inference for Causal Explainability

Weihan Zhang, Zijun Gao; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:1380-1423

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Causal Discovery for Efficient Offline RL with Factored Action Spaces

Cecilia Ehrlichman, Michael Dykstra, Shengpu Tang, Maggie Makar; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:1424-1449

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Causal Process Models: Reframing Dynamic Causal Graph Discovery as a Reinforcement Learning Problem

Turan Orujlu, Christian Gumbsch, Martin V. Butz, Charley M Wu; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:1450-1480

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Intervening to learn and compose causally disentangled representations

Alex Markham, Isaac Hirsch, Jeri A. Chang, Liam Solus, Bryon Aragam; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:1481-1525

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Bayesian Causal Discovery Networks for Linear Mixed Data

Moabi Mokhoro, Ioan Gabriel Bucur, Tom Heskes, Jildau Bouwman, Tom Claassen; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:1526-1544

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Causal Discovery in Action: Learning Chain-Reaction Mechanisms from Interventions

Panayiotis Panayiotou, Özgür Şimşek; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:1545-1571

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Sharp Bounds for Treatment Effect Generalization under Outcome Distribution Shift

Amir Asiaee, Samhita Pal, Cole Beck, Jared Davis Huling; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:1572-1603

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Proxy-Guided Measurement Calibration

Saketh Vishnubhatla, Shu Wan, Andre Harrison, Adrienne Raglin, Huan Liu; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:1604-1634

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Causal and Active Learning-Based Counterfactual Chest X-ray Generation for Supporting Clinical Decision-Making in Lung Disease

Yifei Zhu, Greta Mohr, Lei Zhang, Christopher Sainsbury, Feng Dong, John D Maclay, David J Lowe, David Lagnado, Xujiong Ye; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:1635-1655

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Information-Theoretic Causal Bounds under Unmeasured Confounding

Yonghan Jung, Bogyeong Kang; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:1656-1692

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Differentiable Causal Search

Kaveh Aryan, Hana Chockler, Mohammad Reza Mousavi; Proceedings of the Fifth Conference on Causal Learning and Reasoning, PMLR 323:1693-1708

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