2 papers
stat.ML2025
Near-Optimal Approximations for Bayesian Inference in Function Space
Veit Wild, James Wu, Dino Sejdinovic +1
We propose a scalable inference algorithm for Bayes posteriors defined on a reproducing kernel Hilbert space (RKHS). Given a likelihood function and a Gaussian random element repre…
cs.AI2017
CogSciK: Clustering for Cognitive Science Motivated Decision Making
Dr. W. A. Rivera, James C. Wu
Computational models of decisionmaking must contend with the variance of context and any number of possible decisions that a defined strategic actor can make at a given time. Relyi…