513 citations · 1.1k across the 15 of their papers we have counts for
16 papers
Variational Inference with Gaussian Score Matching
Chirag Modi, Charles Margossian, Yuling Yao +3
Variational inference (VI) is a method to approximate the computationally intractable posterior distributions that arise in Bayesian statistics. Typically, VI fits a simple paramet…
Locking and Quacking: Stacking Bayesian model predictions by log-pooling and superposition
Yuling Yao, Luiz Max Carvalho, Diego Mesquita +1
Combining predictions from different models is a central problem in Bayesian inference and machine learning more broadly. Currently, these predictive distributions are almost exclu…
Discriminative calibration: Check Bayesian computation from simulations and flexible classifier
Yuling Yao, Justin Domke
To check the accuracy of Bayesian computations, it is common to use rank-based simulation-based calibration (SBC). However, SBC has drawbacks: The test statistic is somewhat ad-hoc…
A Cheat Sheet for Bayesian Prediction
Bertrand Clarke, Yuling Yao
This paper reviews the growing field of Bayesian prediction. Bayes point and interval prediction are defined and exemplified and situated in statistical prediction more generally.…
Making the most of imprecise measurements: Changing patterns of arsenic concentrations in shallow wells of Bangladesh from laboratory and field data
Yuling Yao, Rajib Mozumder, Benjamin Bostick +4
Millions of people in Bangladesh drink well water contaminated with arsenic. Despite the severity of this heath crisis, little is known about the extent to which groundwater arseni…
Bayesian hierarchical stacking: Some models are (somewhere) useful
Yuling Yao, Gregor Pirš, Aki Vehtari +1
Stacking is a widely used model averaging technique that asymptotically yields optimal predictions among linear averages. We show that stacking is most effective when model predict…