Table of Contents

• Dual Likelihood for Causal Inference under Structure UncertaintyDavid Strieder, Mathias Drton. 1-17 [doi]
• Ensembled Prediction Intervals for Causal Outcomes Under Hidden ConfoundingMyrl G. Marmarelis, Greg Ver Steeg, Aram Galstyan, Fred Morstatter. 18-40 [doi]
• An Interventional Perspective on Identifiability in Gaussian LTI Systems with Independent Component AnalysisGoutham Rajendran, Patrik Reizinger, Wieland Brendel, Pradeep Kumar Ravikumar. 41-70 [doi]
• Structure Learning with Continuous Optimization: A Sober Look and BeyondIgnavier Ng, Biwei Huang, Kun Zhang 0001. 71-105 [doi]
• Causal State Distillation for Explainable Reinforcement LearningWenhao Lu, Xufeng Zhao, Thilo Fryen, Jae Hee Lee 0001, Mengdi Li, Sven Magg, Stefan Wermter. 106-142 [doi]
• Cautionary Tales on Synthetic Controls in Survival AnalysesAlicia Curth, Hoifung Poon, Aditya V. Nori, Javier González 0002. 143-159 [doi]
• Finding Alignments Between Interpretable Causal Variables and Distributed Neural RepresentationsAtticus Geiger, Zhengxuan Wu, Christopher Potts, Thomas Icard, Noah D. Goodman. 160-187 [doi]
• Fundamental Properties of Causal Entropy and Information GainFrancisco Nunes Ferreira Quialheiro Simoes, Mehdi Dastani, Thijs van Ommen. 188-208 [doi]
• Bicycle: Intervention-Based Causal Discovery with CyclesMartin Rohbeck, Brian Clarke, Katharina Mikulik, Alexandra Pettet, Oliver Stegle, Kai Ueltzhöffer. 209-242 [doi]
• Pragmatic Fairness: Developing Policies with Outcome Disparity ControlLimor Gultchin, Siyuan Guo, Alan Malek, Silvia Chiappa, Ricardo Silva. 243-264 [doi]
• Extracting the Multiscale Causal Backbone of Brain DynamicsGabriele D'Acunto, Francesco Bonchi, Gianmarco De Francisci Morales, Giovanni Petri. 265-295 [doi]
• Towards the Reusability and Compositionality of Causal RepresentationsDavide Talon, Phillip Lippe, Stuart James, Alessio Del Bue, Sara Magliacane. 296-324 [doi]
• Causal Discovery Under Local PrivacyRuta Binkyte, Carlos Antonio Pinzóon, Szilvia Lestyan, Kangsoo Jung, Héber Hwang Arcolezi, Catuscia Palamidessi. 325-383 [doi]
• On the Identifiability of Quantized FactorsVitória Barin Pacela, Kartik Ahuja, Simon Lacoste-Julien, Pascal Vincent. 384-422 [doi]
• Confounded Budgeted Causal BanditsFateme Jamshidi, Jalal Etesami, Negar Kiyavash. 423-461 [doi]
• Causal Optimal Transport of AbstractionsYorgos Felekis, Fabio Massimo Zennaro, Nicola Branchini, Theodoros Damoulas. 462-498 [doi]
• Implicit and Explicit Policy Constraints for Offline Reinforcement LearningYang Liu, Marius Hofert. 499-513 [doi]
• On the Lasso for Graphical Continuous Lyapunov ModelsPhilipp Dettling, Mathias Drton, Mladen Kolar. 514-550 [doi]
• Evaluating and Correcting Performative Effects of Decision Support Systems via Causal Domain ShiftPhilip A. Boeken, Onno Zoeter, Joris M. Mooij. 551-569 [doi]
• On the Impact of Neighbourhood Sampling to Satisfy Sufficiency and Necessity Criteria in Explainable AIUrja Pawar, Christian Beder, Ruairi O'Reilly, Donna O'Shea. 570-586 [doi]
• Designing monitoring strategies for deployed machine learning algorithms: navigating performativity through a causal lensJean Feng, Adarsh Subbaswamy, Alexej Gossmann, Harvineet Singh, Berkman Sahiner, Mi-Ok Kim, Gene Anthony Pennello, Nicholas Petrick, Romain Pirracchio, Fan Xia. 587-608 [doi]
• extttcausalAssembly: Generating Realistic Production Data for Benchmarking Causal DiscoveryKonstantin Göbler, Tobias Windisch, Mathias Drton, Tim Pychynski, Martin Roth, Steffen Sonntag. 609-642 [doi]
• Expediting Reinforcement Learning by Incorporating Knowledge About Temporal Causality in the EnvironmentJan Corazza, Hadi Partovi Aria, Daniel Neider, Zhe Xu 0005. 643-664 [doi]
• Causality for Functional Longitudinal DataAndrew Ying. 665-687 [doi]
• Causal Matching using Random Hyperplane TessellationsAbhishek Dalvi, Neil Ashtekar, Vasant G. Honavar. 688-702 [doi]
• Robustness of Algorithms for Causal Structure Learning to Hyperparameter ChoiceDamian Machlanski, Spyridon Samothrakis, Paul Clarke. 703-739 [doi]
• DiConStruct: Causal Concept-based Explanations through Black-Box DistillationRicardo Miguel de Oliveira Moreira, Jacopo Bono, Mário Cardoso, Pedro Saleiro, Mário A. T. Figueiredo, Pedro Bizarro. 740-768 [doi]
• A causality-inspired plus-minus model for player evaluation in team sportsCaterina De Bacco, Yixin Wang, David M. Blei. 769-792 [doi]
• Inference of nonlinear causal effects with application to TWAS with GWAS summary dataBen Dai, ChunLin Li, Haoran Xue, Wei Pan, Xiaotong Shen. 793-826 [doi]
• Lifted Causal Inference in Relational DomainsMalte Luttermann, Mattis Hartwig, Tanya Braun, Ralf Möller 0001, Marcel Gehrke. 827-842 [doi]
• Identifying Linearly-Mixed Causal Representations from Multi-Node InterventionsSimon Bing, Urmi Ninad, Jonas Wahl, Jakob Runge. 843-867 [doi]
• Toward the Identifiability of Comparative Deep Generative ModelsRomain Lopez, Jan-Christian Hütter, Ehsan Hajiramezanali, Jonathan K. Pritchard, Aviv Regev. 868-912 [doi]
• Estimating the Causal Effect of Early ArXiving on Paper AcceptanceYanai Elazar, Jiayao Zhang 0001, David Wadden, Bo Zhang, Noah A. Smith. 913-933 [doi]
• Sequential Deconfounding for Causal Inference with Unobserved ConfoundersTobias Hatt, Stefan Feuerriegel. 934-956 [doi]
• The PetShop Dataset - Finding Causes of Performance Issues across MicroservicesMichaela Hardt, William Roy Orchard, Patrick Blöbaum, Elke Kirschbaum, Shiva Prasad Kasiviswanathan. 957-978 [doi]
• Bootstrap aggregation and confidence measures to improve time series causal discoveryKevin Debeire, Andreas Gerhardus, Jakob Runge, Veronika Eyring. 979-1007 [doi]
• Low-Rank Approximation of Structural Redundancy for Self-Supervised LearningKang Du, Yu Xiang 0004. 1008-1032 [doi]
• Semiparametric Efficient Inference in Adaptive ExperimentsThomas Cook, Alan Mishler, Aaditya Ramdas. 1033-1064 [doi]
• Hyperparameter Tuning for Causal Inference with Double Machine Learning: A Simulation StudyPhilipp Bach, Oliver Schacht, Victor Chernozhukov, Sven Klaassen, Martin Spindler. 1065-1117 [doi]
• Scalable Counterfactual Distribution Estimation in Multivariate Causal ModelsThong Pham, Shohei Shimizu, Hideitsu Hino, Tam Le. 1118-1140 [doi]
• Causal Imputation for Counterfactual SCMs: Bridging Graphs and Latent Factor ModelsAlvaro Ribot, Chandler Squires, Caroline Uhler. 1141-1175 [doi]
• Causal Layering via Conditional EntropyItai Feigenbaum, Devansh Arpit, Shelby Heinecke, Juan Carlos Niebles, Weiran Yao, Caiming Xiong, Silvio Savarese, Huan Wang. 1176-1191 [doi]
• Meaningful Causal Aggregation and Paradoxical ConfoundingYuchen Zhu, Kailash Budhathoki, Jonas M. Kübler, Dominik Janzing. 1192-1217 [doi]
• Causal discovery in a complex industrial system: A time series benchmarkSøren Wengel Mogensen, Karin Rathsman, Per Nilsson. 1218-1236 [doi]
• Causal Discovery with Mixed Linear and Nonlinear Additive Noise Models: A Scalable ApproachWenqin Liu, Biwei Huang, Erdun Gao, Qiuhong Ke, Howard D. Bondell, Mingming Gong. 1237-1263 [doi]