Causal Inference

Learning Linear Causal Representations from Interventions under General Nonlinear Mixing NeurIPS 2023 Learning Nonlinear Causal Effect via Kernel Anchor Regression UAI 2023 Learning Nonparametric Latent Causal Graphs with Unknown Interventions NeurIPS 2023 Learning Optimal Features via Partial Invariance AAAI 2023 Learning Optimal Group-structured Individualized Treatment Rules with Many Treatments JMLR 2023 Learning Prescriptive ReLU Networks ICML 2023 Learning Relational Causal Models with Cycles through Relational Acyclification AAAI 2023 Learning Robust Graph Neural Networks with Limited Supervision AISTATS 2023 Learning the Effects of Physical Actions in a Multi-modal Environment EACL 2023 Learning to Induce Causal Structure ICLR 2023 Learning Treatment Effects from Observational and Experimental Data AISTATS 2023 LEGO: A Multi-agent Collaborative Framework with Role-playing and Iterative Feedback for Causality Explanation Generation EMNLP 2023 Leveraging Causal Graphs for Blocking in Randomized Experiments CLeaR 2023 Leveraging SE(3) Equivariance for Learning 3D Geometric Shape Assembly ICCV 2023 Lifted Inference with Linear Order Axiom AAAI 2023 LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers EMNLP 2023 Linear Causal Disentanglement via Interventions ICML 2023 Local Causal Discovery for Estimating Causal Effects CLeaR 2023 Logic and Commonsense-Guided Temporal Knowledge Graph Completion AAAI 2023 Logic-induced Diagnostic Reasoning for Semi-supervised Semantic Segmentation ICCV 2023 LogicSeg: Parsing Visual Semantics with Neural Logic Learning and Reasoning ICCV 2023 Look Beneath the Surface: Exploiting Fundamental Symmetry for Sample-Efficient Offline RL NeurIPS 2023 Marginal Density Ratio for Off-Policy Evaluation in Contextual Bandits NeurIPS 2023 MarkQA: A large scale KBQA dataset with numerical reasoning EMNLP 2023 Measuring axiomatic soundness of counterfactual image models ICLR 2023