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"

9 / 9 papers shown

Title
Are you using test log-likelihood correctly? Sameer K. Deshpande Soumya K. Ghosh Tin D. Nguyen Tamara Broderick 39 7 0 01 Dec 2022
A Unifying and Canonical Description of Measure-Preserving Diffusions Alessandro Barp So Takao M. Betancourt Alexis Arnaudon Mark Girolami 24 17 0 06 May 2021
AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC Ruqi Zhang A. Feder Cooper Christopher De Sa 8 18 0 29 Feb 2020
Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling Zhe Gan Chunyuan Li Changyou Chen Yunchen Pu Qinliang Su Lawrence Carin BDL UQCV 53 41 0 23 Nov 2016
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators Changyou Chen Nan Ding Lawrence Carin 40 159 0 21 Oct 2016
Stochastic Bouncy Particle Sampler Ari Pakman D. Gilboa David Carlson Liam Paninski 16 32 0 03 Sep 2016
Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks Chunyuan Li Changyou Chen David Carlson Lawrence Carin ODL BDL 27 320 0 23 Dec 2015
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference Y. Gal Zoubin Ghahramani UQCV BDL 205 745 0 06 Jun 2015
MCMC using Hamiltonian dynamics Radford M. Neal 187 3,267 0 09 Jun 2012