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Volume 236: Causal Learning and Reasoning, 1-3 April 2024, Los Angeles, California, USA

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Editors: Francesco Locatello, Vanessa Didelez

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Dual Likelihood for Causal Inference under Structure Uncertainty

David Strieder, Mathias Drton; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:1-17

Ensembled Prediction Intervals for Causal Outcomes Under Hidden Confounding

Myrl G. Marmarelis, Greg Ver Steeg, Aram Galstyan, Fred Morstatter; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:18-40

An Interventional Perspective on Identifiability in Gaussian LTI Systems with Independent Component Analysis

Goutham Rajendran, Patrik Reizinger, Wieland Brendel, Pradeep Kumar Ravikumar; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:41-70

Structure Learning with Continuous Optimization: A Sober Look and Beyond

Ignavier Ng, Biwei Huang, Kun Zhang; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:71-105

Causal State Distillation for Explainable Reinforcement Learning

Wenhao Lu, Xufeng Zhao, Thilo Fryen, Jae Hee Lee, Mengdi Li, Sven Magg, Stefan Wermter; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:106-142

Cautionary Tales on Synthetic Controls in Survival Analyses

Alicia Curth, Hoifung Poon, Aditya V. Nori, Javier González; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:143-159

Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations

Atticus Geiger, Zhengxuan Wu, Christopher Potts, Thomas Icard, Noah Goodman; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:160-187

Fundamental Properties of Causal Entropy and Information Gain

Francisco N. F. Q. Simoes, Mehdi Dastani, Thijs van Ommen; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:188-208

Bicycle: Intervention-Based Causal Discovery with Cycles

Martin Rohbeck, Brian Clarke, Katharina Mikulik, Alexandra Pettet, Oliver Stegle, Kai Ueltzhöffer; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:209-242

Pragmatic Fairness: Developing Policies with Outcome Disparity Control

Limor Gultchin, Siyuan Guo, Alan Malek, Silvia Chiappa, Ricardo Silva; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:243-264

Extracting the Multiscale Causal Backbone of Brain Dynamics

Gabriele D\textsc\char13Acunto, Francesco Bonchi, Gianmarco De Francisci Morales, Giovanni Petri; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:265-295

Towards the Reusability and Compositionality of Causal Representations

Davide Talon, Phillip Lippe, Stuart James, Alessio Del Bue, Sara Magliacane; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:296-324

Causal Discovery Under Local Privacy

Ruta Binkyte, Carlos Antonio Pinzón, Szilvia Lestyán, Kangsoo Jung, Héber Hwang Arcolezi, Catuscia Palamidessi; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:325-383

On the Identifiability of Quantized Factors

Vitória Barin-Pacela, Kartik Ahuja, Simon Lacoste-Julien, Pascal Vincent; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:384-422

Confounded Budgeted Causal Bandits

Fateme Jamshidi, Jalal Etesami, Negar Kiyavash; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:423-461

Causal Optimal Transport of Abstractions

Yorgos Felekis, Fabio Massimo Zennaro, Nicola Branchini, Theodoros Damoulas; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:462-498

Implicit and Explicit Policy Constraints for Offline Reinforcement Learning

Yang Liu, Marius Hofert; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:499-513

On the Lasso for Graphical Continuous Lyapunov Models

Philipp Dettling, Mathias Drton, Mladen Kolar; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:514-550

Evaluating and Correcting Performative Effects of Decision Support Systems via Causal Domain Shift

Philip Boeken, Onno Zoeter, Joris Mooij; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:551-569

On the Impact of Neighbourhood Sampling to Satisfy Sufficiency and Necessity Criteria in Explainable AI

Urja Pawar, Christian Beder, Ruairi O\textsc\char13Reilly, Donna O\textsc\char13Shea; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:570-586

Designing monitoring strategies for deployed machine learning algorithms: navigating performativity through a causal lens

Jean Feng, Adarsh Subbaswamy, Alexej Gossmann, Harvineet Singh, Berkman Sahiner, Mi-Ok Kim, Gene Anthony Pennello, Nicholas Petrick, Romain Pirracchio, Fan Xia; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:587-608

$\textttcausalAssembly$: Generating Realistic Production Data for Benchmarking Causal Discovery

Konstantin Göbler, Tobias Windisch, Mathias Drton, Tim Pychynski, Martin Roth, Steffen Sonntag; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:609-642

Expediting Reinforcement Learning by Incorporating Knowledge About Temporal Causality in the Environment

Jan Corazza, Hadi Partovi Aria, Daniel Neider, Zhe Xu; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:643-664

Causality for Functional Longitudinal Data

Andrew Ying; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:665-687

Causal Matching using Random Hyperplane Tessellations

Abhishek Dalvi, Neil Ashtekar, Vasant G Honavar; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:688-702

Robustness of Algorithms for Causal Structure Learning to Hyperparameter Choice

Damian Machlanski, Spyridon Samothrakis, Paul S Clarke; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:703-739

DiConStruct: Causal Concept-based Explanations through Black-Box Distillation

Ricardo Miguel de Oliveira Moreira, Jacopo Bono, Mário Cardoso, Pedro Saleiro, Mário A. T. Figueiredo, Pedro Bizarro; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:740-768

A causality-inspired plus-minus model for player evaluation in team sports

Caterina De Bacco, Yixin Wang, David Blei; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:769-792

Inference of nonlinear causal effects with application to TWAS with GWAS summary data

Ben Dai, Chunlin Li, Haoran Xue, Wei Pan, Xiaotong Shen; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:793-826

Lifted Causal Inference in Relational Domains

Malte Luttermann, Mattis Hartwig, Tanya Braun, Ralf Möller, Marcel Gehrke; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:827-842

Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions

Simon Bing, Urmi Ninad, Jonas Wahl, Jakob Runge; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:843-867

Toward the Identifiability of Comparative Deep Generative Models

Romain Lopez, Jan-Christian Huetter, Ehsan Hajiramezanali, Jonathan K Pritchard, Aviv Regev; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:868-912

Estimating the Causal Effect of Early ArXiving on Paper Acceptance

Yanai Elazar, Jiayao Zhang, David Wadden, Bo Zhang, Noah A. Smith; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:913-933

Sequential Deconfounding for Causal Inference with Unobserved Confounders

Tobias Hatt, Stefan Feuerriegel; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:934-956

The PetShop Dataset — Finding Causes of Performance Issues across Microservices

Michaela Hardt, William Roy Orchard, Patrick Blöbaum, Elke Kirschbaum, Shiva Kasiviswanathan; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:957-978

Bootstrap aggregation and confidence measures to improve time series causal discovery

Kevin Debeire, Andreas Gerhardus, Jakob Runge, Veronika Eyring; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:979-1007

Low-Rank Approximation of Structural Redundancy for Self-Supervised Learning

Kang Du, Yu Xiang; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:1008-1032

Semiparametric Efficient Inference in Adaptive Experiments

Thomas Cook, Alan Mishler, Aaditya Ramdas; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:1033-1064

Hyperparameter Tuning for Causal Inference with Double Machine Learning: A Simulation Study

Philipp Bach, Oliver Schacht, Victor Chernozhukov, Sven Klaassen, Martin Spindler; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:1065-1117

Scalable Counterfactual Distribution Estimation in Multivariate Causal Models

Thong Pham, Shohei Shimizu, Hideitsu Hino, Tam Le; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:1118-1140

Causal Imputation for Counterfactual SCMs: Bridging Graphs and Latent Factor Models

Álvaro Ribot, Chandler Squires, Caroline Uhler; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:1141-1175

Causal Layering via Conditional Entropy

Itai Feigenbaum, Devansh Arpit, Shelby Heinecke, Juan Carlos Niebles, Weiran Yao, Caiming Xiong, Silvio Savarese, Huan Wang; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:1176-1191

Meaningful Causal Aggregation and Paradoxical Confounding

Yuchen Zhu, Kailash Budhathoki, Jonas M. Kübler, Dominik Janzing; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:1192-1217

Causal discovery in a complex industrial system: A time series benchmark

Søren Wengel Mogensen, Karin Rathsman, Per Nilsson; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:1218-1236

Causal Discovery with Mixed Linear and Nonlinear Additive Noise Models: A Scalable Approach

Wenqin Liu, Biwei Huang, Erdun Gao, Qiuhong Ke, Howard Bondell, Mingming Gong; Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR 236:1237-1263

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