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Proceedings of Machine Learning Research

Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research
Proceedings of Machine Learning Research
PMLR · 2026-06-02 · via Proceedings of Machine Learning Research

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Volume 177: Conference on Causal Learning and Reasoning, 11-13 April 2022, Sequoia Conference Center, Eureka, CA, USA

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Editors: Bernhard Schölkopf, Caroline Uhler, Kun Zhang

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Filter Authors: Filter Titles:

Relational Causal Models with Cycles: Representation and Reasoning

; 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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