Causal Inference

Learning Counterfactual Representations for Estimating Individual Dose-Response Curves AAAI 2020 Learning Data-Driven Drug-Target-Disease Interaction via Neural Tensor Network IJCAI 2020 Learning Disentangled Representations and Group Structure of Dynamical Environments NeurIPS 2020 Learning Disentangled Representations for CounterFactual Regression ICLR 2020 Learning Dynamical Systems with Side Information L4DC 2020 Learning Joint Nonlinear Effects from Single-variable Interventions in the Presence of Hidden Confounders UAI 2020 Learning Linear Non-Gaussian Causal Models in the Presence of Latent Variables JMLR 2020 Learning Optimal Cyclic Causal Graphs from Interventional Data PGM 2020 Learning Overlapping Representations for the Estimation of Individualized Treatment Effects AISTATS 2020 Learning Robust Decision Policies from Observational Data NeurIPS 2020 Learning Sparse Nonparametric DAGs AISTATS 2020 Learning The Difference That Makes A Difference With Counterfactually-Augmented Data ICLR 2020 Learning to search efficiently for causally near-optimal treatments NeurIPS 2020 Lee at SemEval-2020 Task 5: ALBERT Model Based on the Maximum Ensemble Strategy and Different Data Sampling Methods for Detecting Counterfactual Statements SemEval 2020 LMVE at SemEval-2020 Task 4: Commonsense Validation and Explanation Using Pretraining Language Model SemEval 2020 LogicalFactChecker: Leveraging Logical Operations for Fact Checking with Graph Module Network ACL 2020 Logic-guided Semantic Representation Learning for Zero-Shot Relation Classification COLING 2020 Logics of Allies and Enemies: A Formal Approach to the Dynamics of Social Balance Theory IJCAI 2020 Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect NeurIPS 2020 Machine Number Sense: A Dataset of Visual Arithmetic Problems for Abstract and Relational Reasoning AAAI 2020 Machine Reasoning: Technology, Dilemma and Future EMNLP 2020 MASSIVE: Tractable and Robust Bayesian Learning of Many-Dimensional Instrumental Variable Models UAI 2020 Maximum Likelihood Constraint Inference for Inverse Reinforcement Learning ICLR 2020 Measurement Dependence Inducing Latent Causal Models UAI 2020 Measuring Correlation-to-Causation Exaggeration in Press Releases COLING 2020