independence testing

Optimal Prediction-Augmented Algorithms for Testing Independence of Distributions COLT 2026 On Ranking-based Tests of Independence AISTATS 2024 The Minimax Rate of HSIC Estimation for Translation-Invariant Kernels NeurIPS 2024 Cause-Effect Inference in Location-Scale Noise Models: Maximum Likelihood vs. Independence Testing NeurIPS 2023 Max-Sliced Mutual Information NeurIPS 2023 Sequential Predictive Two-Sample and Independence Testing NeurIPS 2023 Entropy Regularized Optimal Transport Independence Criterion AISTATS 2022 Independence Testing-Based Approach to Causal Discovery under Measurement Error and Linear Non-Gaussian Models NeurIPS 2022 Independence Testing for Bounded Degree Bayesian Networks NeurIPS 2022 Non-parametric inference of relational dependence UAI 2022 Exponentially Improved Dimensionality Reduction for l1: Subspace Embeddings and Independence Testing COLT 2021 Bessel Smoothing and Multi-Distribution Property Estimation COLT 2020 MeDIL: A Python Package for Causal Modelling PGM 2020 Towards Non-Parametric Drift Detection via Dynamic Adapting Window Independence Drift Detection (DAWIDD) ICML 2020 Private Testing of Distributions via Sample Permutations NeurIPS 2019 Triad Constraints for Learning Causal Structure of Latent Variables NeurIPS 2019 Local Private Hypothesis Testing: Chi-Square Tests ICML 2018 An Adaptive Test of Independence with Analytic Kernel Embeddings ICML 2017 Kernel Feature Selection via Conditional Covariance Minimization NeurIPS 2017 Tests of Mutual or Serial Independence of Random Vectors with Applications JMLR 2017 Differentially Private Chi-Squared Hypothesis Testing: Goodness of Fit and Independence Testing ICML 2016 Measuring Dependence Powerfully and Equitably JMLR 2016 Multivariate tests of association based on univariate tests NeurIPS 2016 Relevant Path Separation: A Faster Method for Testing Independencies in Bayesian Networks PGM 2016 A Kernel Test for Three-Variable Interactions NeurIPS 2013