B. Wu, E. Weinstein, and D. Blei. Bayesian Empirical Bayes: Simultaneous Inference from Probabilistic Symmetries arXiv preprint, 2025.
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S. Sheng*,
B. Wu*,
B. Zhu, S. Chewi, and A.-A. Pooladian. Theory and Computation for Structured Variational Inference arXiv preprint, 2025.
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S. Sheng, B. Wu, and A. González Sanz. Mode Collapse of Mean-Field Variational Inference arXiv preprint, 2025.
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S. Sheng, B. Wu, and A. González Sanz. and M.Nutz Stability of Mean-Field Variational Inferenc arXiv preprint, 2025.
arXiv
B. Wu and D. Blei. Extending Mean-Field Variational Inference via Entropic Regularization: Theory and Computation arXiv preprint, 2024.
arXiv
B. Wu*, E. N. Weinstein*, Y. Wang, and D. Blei. Adaptive Nonparametric Perturbations of Parametric Bayesian Models arXiv preprint, 2024.
arXiv
D. R. Kowal and B. Wu. Semiparametric Discrete Data Regression with Monte Carlo Inference and Prediction arXiv preprint, 2021.
arXiv
Publications
B. Wu and C. A. Uribe. Frequentist Guarantees of Distributed (Non)-Bayesian Inference Journal of Machine Learning Research, 2025.
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D. R. Kowal and B. Wu. Monte Carlo Inference for Semiparametric Bayesian Regression Journal of the American Statistical Association, 2025.
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B. Wu, B. Zhu, and D. Blei. Distributionally Robust Posterior Sampling: A Variational Bayes Approach ICLR Workshop on Frontiers in Probabilistic Inference: Learning Meets Sampling, 2025.
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D. R. Kowal and B. Wu. Semiparametric Count Data Regression for Self-Reported Mental Health Biometrics, 2023.
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