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Editors: Mihaela van der Schaar, Cheng Zhang, Dominik Janzing
An Algorithm and Complexity Results for Causal Unit Selection
; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:1-26
Directed Graphical Models and Causal Discovery for Zero-Inflated Data
Shiqing Yu, Mathias Drton, Ali Shojaie; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:27-67
Causal Abstraction with Soft Interventions
Riccardo Massidda, Atticus Geiger, Thomas Icard, Davide Bacciu; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:68-87
Jointly Learning Consistent Causal Abstractions Over Multiple Interventional Distributions
Fabio Massimo Zennaro, Máté Drávucz, Geanina Apachitei, W. Dhammika Widanage, Theodoros Damoulas; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:88-121
Distinguishing Cause from Effect on Categorical Data: The Uniform Channel Model
Mario A. T. Figueiredo, Catarina Oliveira; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:122-141
Stochastic Causal Programming for Bounding Treatment Effects
Kirtan Padh, Jakob Zeitler, David Watson, Matt Kusner, Ricardo Silva, Niki Kilbertus; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:142-176
Backtracking Counterfactuals
Julius Von Kügelgen, Abdirisak Mohamed, Sander Beckers; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:177-196
Generalizing Clinical Trials with Convex Hulls
Eric Strobl, Thomas A Lasko; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:197-221
Leveraging Causal Graphs for Blocking in Randomized Experiments
Abhishek Kumar Umrawal; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:222-242
Enhancing Causal Discovery from Robot Sensor Data in Dynamic Scenarios
Luca Castri, Sariah Mghames, Marc Hanheide, Nicola Bellotto; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:243-258
Practical Algorithms for Orientations of Partially Directed Graphical Models
Malte Luttermann, Marcel Wienöbst, Maciej Liskiewicz; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:259-280
Unsupervised Object Learning via Common Fate
Matthias Tangemann, Steffen Schneider, Julius Von Kügelgen, Francesco Locatello, Peter Vincent Gehler, Thomas Brox, Matthias Kuemmerer, Matthias Bethge, Bernhard Schölkopf; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:281-327
On the Interventional Kullback-Leibler Divergence
Jonas Bernhard Wildberger, Siyuan Guo, Arnab Bhattacharyya, Bernhard Schölkopf; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:328-349
Factual Observation Based Heterogeneity Learning for Counterfactual Prediction
Hao Zou, Haotian Wang, Renzhe Xu, Bo Li, Jian Pei, Ye Jun Jian, Peng Cui; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:350-370
Causal Inference under Interference and Model Uncertainty
Chi Zhang, Karthika Mohan, Judea Pearl; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:371-385
Can Active Sampling Reduce Causal Confusion in Offline Reinforcement Learning?
Gunshi Gupta, Tim G. J. Rudner, Rowan Thomas McAllister, Adrien Gaidon, Yarin Gal; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:386-407
Local Causal Discovery for Estimating Causal Effects
Shantanu Gupta, David Childers, Zachary Chase Lipton; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:408-447
On Discovery of Local Independence over Continuous Variables via Neural Contextual Decomposition
Inwoo Hwang, Yunhyeok Kwak, Yeon-Ji Song, Byoung-Tak Zhang, Sanghack Lee; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:448-472
Evaluating Temporal Observation-Based Causal Discovery Techniques Applied to Road Driver Behaviour
Rhys Peter Matthew Howard, Lars Kunze; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:473-498
Influence-Aware Attention for Multivariate Temporal Point Processes
Xiao Shou, Tian Gao, Dharmashankar Subramanian, Debarun Bhattacharjya, Kristin Bennett; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:499-517
Causal Learning through Deliberate Undersampling
Kseniya Solovyeva, David Danks, Mohammadsajad Abavisani, Sergey Plis; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:518-530
Image-based Treatment Effect Heterogeneity
Connor Thomas Jerzak, Fredrik Daniel Johansson, Adel Daoud; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:531-552
Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning
Yuejiang Liu, Alexandre Alahi, Chris Russell, Max Horn, Dominik Zietlow, Bernhard Schölkopf, Francesco Locatello; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:553-573
Causal Inference Despite Limited Global Confounding via Mixture Models
Spencer L. Gordon, Bijan Mazaheri, Yuval Rabani, Leonard Schulman; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:574-601
A Meta-Reinforcement Learning Algorithm for Causal Discovery
Andreas W.M. Sauter, Erman Acar, Vincent Francois-Lavet; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:602-619
Instrumental Processes Using Integrated Covariances
Søren Wengel Mogensen; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:620-641
Branch-Price-and-Cut for Causal Discovery
James Cussens; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:642-661
Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling
Romain Lopez, Natasa Tagasovska, Stephen Ra, Kyunghyun Cho, Jonathan Pritchard, Aviv Regev; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:662-691
Learning Conditional Granger Causal Temporal Networks
Ananth Balashankar, Srikanth Jagabathula, Lakshmi Subramanian; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:692-706
Beyond the Markov Equivalence Class: Extending Causal Discovery under Latent Confounding
Mirthe Maria Van Diepen, Ioan Gabriel Bucur, Tom Heskes, Tom Claassen; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:707-725
Causal Discovery with Score Matching on Additive Models with Arbitrary Noise
Francesco Montagna, Nicoletta Noceti, Lorenzo Rosasco, Kun Zhang, Francesco Locatello; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:726-751
Scalable Causal Discovery with Score Matching
Francesco Montagna, Nicoletta Noceti, Lorenzo Rosasco, Kun Zhang, Francesco Locatello; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:752-771
Local Dependence Graphs for Discrete Time Processes
Wojciech Niemiro, Łukasz Rajkowski; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:772-790
Estimating long-term causal effects from short-term experiments and long-term observational data with unobserved confounding
Graham Van Goffrier, Lucas Maystre, Ciarán Mark Gilligan-Lee; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:791-813
Factorization of the Partial Covariance in Singly-Connected Path Diagrams
Jose Peña; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:814-849
Non-parametric identifiability and sensitivity analysis of synthetic control models
Jakob Zeitler, Athanasios Vlontzos, Ciarán Mark Gilligan-Lee; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:850-865
Causal Models with Constraints
Sander Beckers, Joseph Halpern, Christopher Hitchcock; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:866-879
Causal Discovery for Non-stationary Non-linear Time Series Data Using Just-In-Time Modeling
Daigo Fujiwara, Kazuki Koyama, Keisuke Kiritoshi, Tomomi Okawachi, Tomonori Izumitani, Shohei Shimizu; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:880-894
Sample-Specific Root Causal Inference with Latent Variables
Eric Strobl, Thomas A Lasko; Proceedings of the Second Conference on Causal Learning and Reasoning, PMLR 213:895-915
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