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 Bayesian neural networks via MCMC: a Python-based tutorialIEEE Access (IEEE Access), 2023 |
 Meta-learning Control Variates: Variance Reduction with Limited DataConference on Uncertainty in Artificial Intelligence (UAI), 2023 |
 Kernel Stein Discrepancy thinning: a theoretical perspective of
pathologies and a practical fix with regularizationNeural Information Processing Systems (NeurIPS), 2023 |
 Multivariate strong invariance principles in Markov chain Monte CarloElectronic Journal of Statistics (EJS), 2022 |
 Doubly Robust Stein-Kernelized Monte Carlo Estimator: Simultaneous
Bias-Variance Reduction and Supercanonical ConvergenceJournal of machine learning research (JMLR), 2021 |
 Statistical Depth Meets Machine Learning: Kernel Mean Embeddings and
Depth in Functional Data AnalysisInternational Statistical Review (ISR), 2021 |
 Variance reduction for additive functional of Markov chains via
martingale representationsStatistics and computing (Stat. Comput.), 2019 |
