causal inference

Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs NeurIPS 2022 Learning Causal Models from Conditional Moment Restrictions by Importance Weighting ICLR 2022 Learning Cluster Causal Diagrams: An Information-Theoretic Approach IJCAI 2022 Learning from Counterfactual Links for Link Prediction ICML 2022 Learning Human Driving Behaviors with Sequential Causal Imitation Learning AAAI 2022 Learning Temporally Causal Latent Processes from General Temporal Data ICLR 2022 Linear Combinatorial Semi-Bandit with Causally Related Rewards IJCAI 2022 LOG: Active Model Adaptation for Label-Efficient OOD Generalization NeurIPS 2022 MALTS: Matching After Learning to Stretch JMLR 2022 Markovian Interference in Experiments NeurIPS 2022 Matching Learned Causal Effects of Neural Networks with Domain Priors ICML 2022 Measuring the Effect of Training Data on Deep Learning Predictions via Randomized Experiments ICML 2022 Minimum Cost Intervention Design for Causal Effect Identification ICML 2022 Mitigating Spurious Correlation in Natural Language Understanding with Counterfactual Inference EMNLP 2022 Multi-Instance Causal Representation Learning for Instance Label Prediction and Out-of-Distribution Generalization NeurIPS 2022 Neural score matching for high-dimensional causal inference AISTATS 2022 Non-parametric inference of relational dependence UAI 2022 Obtaining Causal Information by Merging Datasets with MAXENT AISTATS 2022 Off-Policy Evaluation for Episodic Partially Observable Markov Decision Processes under Non-Parametric Models NeurIPS 2022 Off-Policy Evaluation with Deficient Support Using Side Information NeurIPS 2022 Off-Policy Evaluation with Policy-Dependent Optimization Response NeurIPS 2022 On Causally Disentangled Representations AAAI 2022 On Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning ICLR 2022 On Instrumental Variable Regression for Deep Offline Policy Evaluation JMLR 2022 Online Balanced Experimental Design ICML 2022