3.9k citations · 11.2k across the 144 of their papers we have counts for
149 papers
Simulation-Based Empirical Bayes
Xinwei Shen, Diana Cai, Cheng Zhang +1
Empirical Bayes (EB) performs simultaneous inference across many related latent variables. Classical EB assumes that the likelihood p(x | z) is tractable. In many scientific applic…
Geometric Causal Models
Eli N. Weinstein, David M. Blei
Scientists often seek to draw causal inferences from structured data that is not independently and identically distributed, such as spatial data, network data, or molecular data. W…
Bayesian Empirical Bayes: Simultaneous Inference from Probabilistic Symmetries
Bohan Wu, Eli N. Weinstein, David M. Blei
Empirical Bayes (EB) improves the accuracy of simultaneous inference "by learning from the experience of others" (Efron, 2012). Classical EB theory focuses on latent variables that…
The Sequential Nature of Science: Quantifying Learning from a Sequence of Studies
Jonas M. Mikhaeil, Donald P. Green, David Blei
Scientific progress is inherently sequential: collective knowledge is updated as new studies enter the literature. We propose the sequential meta-analysis research trace (SMART), w…
Fisher meets Feynman: score-based variational inference with a product of experts
Diana Cai, Robert M. Gower, David M. Blei +1
We introduce a highly expressive yet distinctly tractable family for black-box variational inference (BBVI). Each member of this family is a weighted product of experts (PoE), and…
Bayesian Invariance Modeling of Multi-Environment Data
Luhuan Wu, Mingzhang Yin, Yixin Wang +2
Invariant prediction [Peters et al., 2016] analyzes feature/outcome data from multiple environments to identify invariant features - those with a stable predictive relationship to…