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Causal Inference

934 directly classified papers

Papers per year

Papers

Learning Causal Effects via Weighted Empirical Risk Minimization NIPS 2020
Entropic Causal Inference: Identifiability and Finite Sample Results NIPS 2020
Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs NIPS 2020
Minimax Optimal Nonparametric Estimation of Heterogeneous Treatment Effects NIPS 2020
Joint Causal Inference from Multiple Contexts JMLR 2020
Local Causal Network Learning for Finding Pairs of Total and Direct Effects JMLR 2020
General Control Functions for Causal Effect Estimation from IVs NIPS 2020
Towards Scalable Bayesian Learning of Causal DAGs NIPS 2020
Multi-task Causal Learning with Gaussian Processes NIPS 2020
Generative causal explanations of black-box classifiers NIPS 2020
Identification and Estimation of Causal Effects Defined by Shift Interventions UAI 2020
High-Dimensional Poisson Structural Equation Model Learning via $\ell_1$-Regularized Regression JMLR 2019
Distributed Representation of Words in Cause and Effect Spaces AAAI 2019
Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise JMLR 2019
Domain-Size Aware Markov Logic Networks AISTATS 2019
Semi-Generative Modelling: Covariate-Shift Adaptation with Cause and Effect Features AISTATS 2019
Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning IJCNLP 2019
KagNet: Knowledge-Aware Graph Networks for Commonsense Reasoning IJCNLP 2019
Adapting Meta Knowledge Graph Information for Multi-Hop Reasoning over Few-Shot Relations IJCNLP 2019
Weakly Supervised Multilingual Causality Extraction from Wikipedia IJCNLP 2019
Intervening on Network Ties UAI 2019
Finding Minimal d-separators in Linear Time and Applications UAI 2019
Weakly Supervised Multilingual Causality Extraction from Wikipedia EMNLP 2019
Are Disentangled Representations Helpful for Abstract Visual Reasoning? NIPS 2019
Knowledge Aware Conversation Generation with Explainable Reasoning over Augmented Graphs EMNLP 2019