Relational Causal Models with Cycles: Representation and Reasoning

Ragib Ahsan, David Arbour, Elena Zheleva; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:1-18

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Towards efficient representation identification in supervised learning

Kartik Ahuja, Divyat Mahajan, Vasilis Syrgkanis, Ioannis Mitliagkas; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:19-43

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Weakly Supervised Discovery of Semantic Attributes

Ameen Ali Ali, Tomer Galanti, Evgenii Zheltonozhskii, Chaim Baskin, Lior Wolf; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:44-69

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VIM: Variational Independent Modules for Video Prediction

Rim Assouel, Lluis Castrejon, Aaron Courville, Nicolas Ballas, Yoshua Bengio; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:70-89

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Causal Explanations and XAI

Sander Beckers; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:90-109

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Cause-effect inference through spectral independence in linear dynamical systems: theoretical foundations

Michel Besserve, Naji Shajarisales, Dominik Janzing, Bernhard Schölkopf; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:110-143

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Process Independence Testing in Proximal Graphical Event Models

Debarun Bhattacharjya, Karthikeyan Shanmugam, Tian Gao, Dharmashankar Subramanian; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:144-161

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Typing assumptions improve identification in causal discovery

PHILIPPE BROUILLARD, Perouz Taslakian, Alexandre Lacoste, Sebastien Lachapelle, Alexandre Drouin; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:162-177

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Disentangling Controlled Effects for Hierarchical Reinforcement Learning

Oriol Corcoll, Raul Vicente; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:178-200

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Interactive rank testing by betting

Boyan Duan, Aaditya Ramdas, Larry Wasserman; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:201-235

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Bivariate Causal Discovery via Conditional Divergence

Bao Duong, Thin Nguyen; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:236-252

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Differentiable Causal Discovery Under Latent Interventions

Gonçalo Rui Alves Faria, Andre Martins, Mario A. T. Figueiredo; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:253-274

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Selection, Ignorability and Challenges With Causal Fairness

Jake Fawkes, Robin Evans, Dino Sejdinovic; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:275-289

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Learning Invariant Representations with Missing Data

Mark Goldstein, Joern-Henrik Jacobsen, Olina Chau, Adriel Saporta, Aahlad Manas Puli, Rajesh Ranganath, Andrew Miller; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:290-301

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Info Intervention and its Causal Calculus

Heyang Gong, ke zhu; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:302-317

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Partial Identification with Noisy Covariates: A Robust Optimization Approach

Wenshuo Guo, Mingzhang Yin, Yixin Wang, Michael Jordan; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:318-335

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Simple data balancing achieves competitive worst-group-accuracy

Badr Youbi Idrissi, Martin Arjovsky, Mohammad Pezeshki, David Lopez-Paz; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:336-351

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Predictive State Propensity Subclassification (PSPS): A causal inference algorithm for data-driven propensity score stratification

Joseph Kelly, Jing Kong, Georg M. Goerg; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:352-372

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Non-parametric Inference Adaptive to Intrinsic Dimension

Khashayar Khosravi, Greg Lewis, Vasilis Syrgkanis; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:373-389

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Learning Causal Overhypotheses through Exploration in Children and Computational Models

Eliza Kosoy, Adrian Liu, Jasmine L Collins, David Chan, Jessica B Hamrick, Nan Rosemary Ke, Sandy Huang, Bryanna Kaufmann, John Canny, Alison Gopnik; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:390-406

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Causal Bandits without prior knowledge using separating sets

Arnoud De Kroon, Joris Mooij, Danielle Belgrave; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:407-427

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Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA

Sebastien Lachapelle, Pau Rodriguez, Yash Sharma, Katie E Everett, Rémi LE PRIOL, Alexandre Lacoste, Simon Lacoste-Julien; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:428-484

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Data-driven exclusion criteria for instrumental variable studies

Tony Liu, Patrick Lawlor, Lyle Ungar, Konrad Kording; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:485-508

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Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data

Sindy Löwe, David Madras, Richard Zemel, Max Welling; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:509-525

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Efficient Reinforcement Learning with Prior Causal Knowledge

Yangyi Lu, Amirhossein Meisami, Ambuj Tewari; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:526-541

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A Distance Covariance-based Kernel for Nonlinear Causal Clustering in Heterogeneous Populations

Alex Markham, Richeek Das, Moritz Grosse-Wentrup; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:542-558

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CausalCity: Complex Simulations with Agency for Causal Discovery and Reasoning

Daniel McDuff, Yale Song, Jiyoung Lee, Vibhav Vineet, Sai Vemprala, Nicholas Alexander Gyde, Hadi Salman, Shuang Ma, Kwanghoon Sohn, Ashish Kapoor; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:559-575

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Equality Constraints in Linear Hawkes Processes

Søren Wengel Mogensen; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:576-593

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Optimal Training of Fair Predictive Models

Razieh Nabi, Daniel Malinsky, Ilya Shpitser; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:594-617

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Differentially Private Estimation of Heterogeneous Causal Effects

Fengshi Niu, Harsha Nori, Brian Quistorff, Rich Caruana, Donald Ngwe, Aadharsh Kannan; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:618-633

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On the Equivalence of Causal Models: A Category-Theoretic Approach

Jun Otsuka, Hayato Saigo; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:634-646

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Diffusion Causal Models for Counterfactual Estimation

Pedro Sanchez, Sotirios A. Tsaftaris; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:647-668

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Causal Structure Discovery between Clusters of Nodes Induced by Latent Factors

Chandler Squires, Annie Yun, Eshaan Nichani, Raj Agrawal, Caroline Uhler; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:669-687

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Causal Imputation via Synthetic Interventions

Chandler Squires, Dennis Shen, Anish Agarwal, Devavrat Shah, Caroline Uhler; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:688-711

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Estimating Social Influence from Observational Data

Dhanya Sridhar, Caterina De Bacco, David Blei; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:712-733

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Identifying Principal Stratum Causal Effects Conditional on a Post-treatment Intermediate Response

Xiaoqing Tan, Judah Abberbock, Priya Rastogi, Gong Tang; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:734-753

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Attainability and Optimality: The Equalized Odds Fairness Revisited

Zeyu Tang, Kun Zhang; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:754-786

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Same Cause; Different Effects in the Brain

Mariya Toneva, Jennifer Williams, Anand Bollu, Christoph Dann, Leila Wehbe; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:787-825

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A Multivariate Causal Discovery based on Post-Nonlinear Model

Kento Uemura, Takuya Takagi, Kambayashi Takayuki, Hiroyuki Yoshida, Shohei Shimizu; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:826-839

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Local Constraint-Based Causal Discovery under Selection Bias

Philip Versteeg, Joris Mooij, Cheng Zhang; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:840-860

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A Uniformly Consistent Estimator of non-Gaussian Causal Effects Under the $k$-Triangle-Faithfulness Assumption

Shuyan Wang, Peter Spirtes; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:861-876

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Identifying Coarse-grained Independent Causal Mechanisms with Self-supervision

Xiaoyang Wang, Klara Nahrstedt, Oluwasanmi O Koyejo; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:877-903

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Integrative $R$-learner of heterogeneous treatment effects combining experimental and observational studies

Lili Wu, Shu Yang; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:904-926

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Fair Classification with Instance-dependent Label Noise

Songhua Wu, Mingming Gong, Bo Han, Yang Liu, Tongliang Liu; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:927-943

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Causal Discovery in Linear Structural Causal Models with Deterministic Relations

Yuqin Yang, Mohamed S Nafea, AmirEmad Ghassami, Negar Kiyavash; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:944-993

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Causal Discovery for Linear Mixed Data

Yan Zeng, Shohei Shimizu, Hidetoshi Matsui, Fuchun Sun; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:994-1009

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Can Humans Be out of the Loop?

Junzhe Zhang, Elias Bareinboim; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:1010-1025

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Some Reflections on Drawing Causal Inference using Textual Data: Parallels Between Human Subjects and Organized Texts

Bo Zhang, Jiayao Zhang; Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:1026-1036

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