Causal Inference

Improving Commonsense Question Answering by Graph-based Iterative Retrieval over Multiple Knowledge Sources COLING 2020 Improving Event Duration Prediction via Time-aware Pre-training EMNLP 2020 Improving Medical NLI Using Context-Aware Domain Knowledge COLING 2020 Inference of Dynamic Graph Changes for Functional Connectome AISTATS 2020 Information Theoretic Counterfactual Learning from Missing-Not-At-Random Feedback NeurIPS 2020 Integrating knowledge graph embeddings to improve mention representation for bridging anaphora resolution COLING 2020 Integrating Overlapping Datasets Using Bivariate Causal Discovery AAAI 2020 Interventional Few-Shot Learning NeurIPS 2020 Invariant Causal Prediction for Block MDPs ICML 2020 Invariant Rationalization ICML 2020 Inverse Active Sensing: Modeling and Understanding Timely Decision-Making ICML 2020 Inverse Rational Control with Partially Observable Continuous Nonlinear Dynamics NeurIPS 2020 Investigating Matureness of Probabilistic Graphical Models for Dry-Bulk Shipping PGM 2020 ISIKUN at the FinCausal 2020: Linguistically informed Machine-learning Approach for Causality Identification in Financial Documents COLING 2020 Ivy: Instrumental Variable Synthesis for Causal Inference AISTATS 2020 Joint Causal Inference from Multiple Contexts JMLR 2020 Kernel-based Approach for Learning Causal Graphs from Mixed Data PGM 2020 Kernel Conditional Moment Test via Maximum Moment Restriction UAI 2020 Knowing-How under Uncertainty (Extended Abstract) IJCAI 2020 Knowledge Transfer for Learning Markov Equivalence Classes PGM 2020 LangResearchLab_NC at FinCausal 2020, Task 1: A Knowledge Induced Neural Net for Causality Detection COLING 2020 LazyIter: A Fast Algorithm for Counting Markov Equivalent DAGs and Designing Experiments ICML 2020 Learning and Reasoning for Robot Sequential Decision Making under Uncertainty AAAI 2020 Learning and Sampling of Atomic Interventions from Observations ICML 2020 Learning Causal Networks via Additive Faithfulness JMLR 2020