The promises and pitfalls of Stochastic Gradient Langevin Dynamics

25 November 2018

Papers citing "The promises and pitfalls of Stochastic Gradient Langevin Dynamics"

10 / 60 papers shown

Title
On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation N. Brosse C. Riquelme Alice Martin Sylvain Gelly Eric Moulines BDL OOD UQCV 97 34 0 22 Jan 2020
Aggregated Gradient Langevin Dynamics Chao Zhang Jiahao Xie Zebang Shen P. Zhao Tengfei Zhou Hui Qian 81 1 0 21 Oct 2019
Nonasymptotic estimates for Stochastic Gradient Langevin Dynamics under local conditions in nonconvex optimization Ying Zhang Ömer Deniz Akyildiz Theodoros Damoulas Sotirios Sabanis 104 47 0 04 Oct 2019
Partitioned integrators for thermodynamic parameterization of neural networks Benedict Leimkuhler Charles Matthews Tiffany J. Vlaar ODL 63 22 0 30 Aug 2019
Stochastic gradient Markov chain Monte Carlo Christopher Nemeth Paul Fearnhead BDL 81 139 0 16 Jul 2019
Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting Maxime Vono Daniel Paulin Arnaud Doucet 132 37 0 23 May 2019
Revisiting clustering as matrix factorisation on the Stiefel manifold Stéphane Chrétien Benjamin Guedj 46 3 0 11 Mar 2019
Scalable Metropolis-Hastings for Exact Bayesian Inference with Large Datasets R. Cornish Paul Vanetti Alexandre Bouchard-Côté George Deligiannidis Arnaud Doucet 109 17 0 28 Jan 2019
Hamiltonian Monte Carlo with Energy Conserving Subsampling Khue-Dung Dang M. Quiroz Robert Kohn Minh-Ngoc Tran M. Villani 120 62 0 02 Aug 2017
Quasi-stationary Monte Carlo and the ScaLE Algorithm M. Pollock Paul Fearnhead A. M. Johansen Gareth O. Roberts 98 18 0 12 Sep 2016