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conftrace_

average treatment effect

61 papers

ATE

Papers

Bounding causal effects with leaky instruments UAI 2024 Causal ATE Mitigates Unintended Bias in Controlled Text Generation CoNLL 2024 Causal Inference for Human-Language Model Collaboration NAACL 2024 Cluster-Adaptive Network A/B Testing: From Randomization to Estimation JMLR 2024 Conditional Outcome Equivalence: A Quantile Alternative to CATE NeurIPS 2024 Federated Experiment Design under Distributed Differential Privacy AISTATS 2024 Limits of Approximating the Median Treatment Effect COLT 2024 Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around Exposure-Outcome Pairs UAI 2024 Marginal Causal Flows for Validation and Inference NeurIPS 2024 Proximal Causal Inference for Synthetic Control with Surrogates AISTATS 2024 Semiparametric Efficient Inference in Adaptive Experiments CLeaR 2024 Smaller Confidence Intervals From IPW Estimators via Data-Dependent Coarsening (Extended Abstract) COLT 2024 A/B Testing in Network Data with Covariate-Adaptive Randomization ICML 2023 A Reinforcement Learning Framework for Dynamic Mediation Analysis ICML 2023 Average Adjusted Association: Efficient Estimation with High Dimensional Confounders AISTATS 2023 Double and Single Descent in Causal Inference with an Application to High-Dimensional Synthetic Control NeurIPS 2023 Finite Population Regression Adjustment and Non-asymptotic Guarantees for Treatment Effect Estimation NeurIPS 2023 Local Causal Discovery for Estimating Causal Effects CLeaR 2023 Marginal Density Ratio for Off-Policy Evaluation in Contextual Bandits NeurIPS 2023 Non-stationary Experimental Design under Linear Trends NeurIPS 2023 Sharp Bounds for Generalized Causal Sensitivity Analysis NeurIPS 2023 Conceptualizing Treatment Leakage in Text-based Causal Inference NAACL 2022 Debiased Causal Tree: Heterogeneous Treatment Effects Estimation with Unmeasured Confounding NeurIPS 2022 Partial Identification of Treatment Effects with Implicit Generative Models NeurIPS 2022 Partial Identification with Noisy Covariates: A Robust Optimization Approach CLeaR 2022