double machine learning

Automatic debiased machine learning and sensitivity analysis for sample selection models CLeaR 2026 Does Topic Sentiment Cause Perceived Ideology? Comparing Human and LLM Annotations in Political News Articles ACL 2026 Valid Inference for Treatment Effects under Multimodal Confounding CLeaR 2026 Adjustment for Confounding using Pre-Trained Representations ICML 2025 Double Debiased Machine Learning for Mediation Analysis with Continuous Treatments AISTATS 2025 Double Machine Learning for Causal Inference under Shared-State Interference ICML 2025 Graph Machine Learning based Doubly Robust Estimator for Network Causal Effects AISTATS 2025 Automated Efficient Estimation using Monte Carlo Efficient Influence Functions NeurIPS 2024 DoubleLingo: Causal Estimation with Large Language Models NAACL 2024 Hyperparameter Tuning for Causal Inference with Double Machine Learning: A Simulation Study CLeaR 2024 Learning Decision Policies with Instrumental Variables through Double Machine Learning ICML 2024 On Doubly Robust Inference for Double Machine Learning in Semiparametric Regression JMLR 2024 The Causal Impact of Credit Lines on Spending Distributions AAAI 2024 Average Adjusted Association: Efficient Estimation with High Dimensional Confounders AISTATS 2023 Mitigating Adversarial Vulnerability through Causal Parameter Estimation by Adversarial Double Machine Learning ICCV 2023 Coordinated Double Machine Learning ICML 2022 DoubleML - An Object-Oriented Implementation of Double Machine Learning in Python JMLR 2022 Orthogonal Statistical Learning with Self-Concordant Loss COLT 2022 Double/Debiased Machine Learning for Dynamic Treatment Effects NeurIPS 2021 Double Machine Learning Density Estimation for Local Treatment Effects with Instruments NeurIPS 2021 Estimating Identifiable Causal Effects on Markov Equivalence Class through Double Machine Learning ICML 2021 Estimating Identifiable Causal Effects through Double Machine Learning AAAI 2021 Orthogonal Machine Learning: Power and Limitations ICML 2018