124 citations · 279 across the 11 of their papers we have counts for
4 papers · 1 filter
High-Order Stochastic Gradient Thermostats for Bayesian Learning of Deep Models
Chunyuan Li, Changyou Chen, Kai Fan +1
Learning in deep models using Bayesian methods has generated significant attention recently. This is largely because of the feasibility of modern Bayesian methods to yield scalable…
-means: Fighting against Degeneracy in Sequential Monte Carlo with an Application to Tracking
Kai Fan, Katherine Heller
For regular particle filter algorithm or Sequential Monte Carlo (SMC) methods, the initial weights are traditionally dependent on the proposed distribution, the posterior distribut…
Fast Second-Order Stochastic Backpropagation for Variational Inference
Kai Fan, Ziteng Wang, Jeff Beck +2
We propose a second-order (Hessian or Hessian-free) based optimization method for variational inference inspired by Gaussian backpropagation, and argue that quasi-Newton optimizati…
Bayesian Models for Heterogeneous Personalized Health Data
Kai Fan, Allison E. Aiello, Katherine A. Heller
The purpose of this study is to leverage modern technology (such as mobile or web apps in Beckman et al. (2014)) to enrich epidemiology data and infer the transmission of disease.…