7 papers
The Influence Function of Transport-based Quantiles
Alberto González-Sanz, Shunan Sheng, Bohan Wu +1
Transport-based quantiles extend univariate quantiles to multivariate distributions via optimal transport. We study the influence function of the transport quantile map $\mathbf{Q}…
Environment-Robust Representation Learning with Empirical Bayes
Yuli Slavutsky, Matthew Shen, Bohan Wu +1
We consider multi-environment prediction problems. We assume the environments change the distribution of a latent variable, while the mechanisms generating observed covariates and…
The Illusion of Learning from Observational Data: An Empirical Bayes Perspective
Bohan Wu, Sebastian Salazar, Donald P. Green +1
Randomized experiments have long been the gold standard for scientists seeking to learn about cause and effect. When randomized experiments are infeasible, scientists often resort…
Extending Mean-Field Variational Inference via Entropic Regularization: Theory and Computation
Bohan Wu, David Blei
Variational inference (VI) has emerged as a popular method for approximate inference for high-dimensional Bayesian models. In this paper, we propose a novel VI method that extends…
Theory and computation for structured variational inference
Shunan Sheng, Bohan Wu, Bennett Zhu +2
Structured variational inference constitutes a core methodology in modern statistical applications. Unlike mean-field variational inference, the approximate posterior is assumed to…
Mode Collapse of Mean-Field Variational Inference
Shunan Sheng, Bohan Wu, Alberto González-Sanz
Mean-field variational inference (MFVI) is a widely used method for approximating high-dimensional probability distributions by product measures. It has been empirically observed t…