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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
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
Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:19-43
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Weakly Supervised Discovery of Semantic Attributes
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
Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:70-89
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Causal Explanations and XAI
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
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
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
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
Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:178-200
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Interactive rank testing by betting
Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:201-235
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Bivariate Causal Discovery via Conditional Divergence
Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:236-252
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Differentiable Causal Discovery Under Latent Interventions
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
Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:275-289
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Learning Invariant Representations with Missing Data
Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:290-301
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Info Intervention and its Causal Calculus
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
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
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
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
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
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
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
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
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
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
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
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
Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:559-575
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Equality Constraints in Linear Hawkes Processes
Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:576-593
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Optimal Training of Fair Predictive Models
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
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
Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:634-646
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Diffusion Causal Models for Counterfactual Estimation
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
Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:669-687
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Causal Imputation via Synthetic Interventions
Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:688-711
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Estimating Social Influence from Observational Data
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
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
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
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
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
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
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
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
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
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
Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:944-993
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Causal Discovery for Linear Mixed Data
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?
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
Proceedings of the First Conference on Causal Learning and Reasoning, PMLR 177:1026-1036
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