12 citations · 53 across the 25 of their papers we have counts for
3 papers · 1 filter
On the Consistency of Graph-based Bayesian Learning and the Scalability of Sampling Algorithms
Nicolas Garcia Trillos, Zachary Kaplan, Thabo Samakhoana +1
A popular approach to semi-supervised learning proceeds by endowing the input data with a graph structure in order to extract geometric information and incorporate it into a Bayesi…
Continuum Limit of Posteriors in Graph Bayesian Inverse Problems
Nicolas Garcia Trillos, Daniel Sanz-Alonso
We consider the problem of recovering a function input of a differential equation formulated on an unknown domain . We assume to have access to a discrete domain $M_n=\{x_1, \do…
The Bayesian update: variational formulations and gradient flows
Nicolas Garcia Trillos, Daniel Sanz-Alonso
The Bayesian update can be viewed as a variational problem by characterizing the posterior as the minimizer of a functional. The variational viewpoint is far from new and is at the…