High-Order Stochastic Gradient Thermostats for Bayesian Learning of Deep
Models

High-Order Stochastic Gradient Thermostats for Bayesian Learning of Deep Models

23 December 2015

Lawrence Carin

Papers citing "High-Order Stochastic Gradient Thermostats for Bayesian Learning of Deep Models"

7 / 7 papers shown

Title
Are you using test log-likelihood correctly? Sameer K. Deshpande Soumya K. Ghosh Tin D. Nguyen Tamara Broderick 24 7 0 01 Dec 2022
A Unifying and Canonical Description of Measure-Preserving Diffusions Alessandro Barp So Takao M. Betancourt Alexis Arnaudon Mark Girolami 17 17 0 06 May 2021
Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling Zhe Gan Chunyuan Li Changyou Chen Yunchen Pu Qinliang Su Lawrence Carin BDL UQCV 37 41 0 23 Nov 2016
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators Changyou Chen Nan Ding Lawrence Carin 32 158 0 21 Oct 2016
Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks Chunyuan Li Changyou Chen David Carlson Lawrence Carin ODL BDL 19 319 0 23 Dec 2015
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference Y. Gal Zoubin Ghahramani UQCV BDL 197 745 0 06 Jun 2015
MCMC using Hamiltonian dynamics Radford M. Neal 176 3,260 0 09 Jun 2012