Bridging the Gap between Stochastic Gradient MCMC and Stochastic Optimization

25 December 2015

David Carlson

Lawrence Carin

Papers citing "Bridging the Gap between Stochastic Gradient MCMC and Stochastic Optimization"

20 / 20 papers shown

Title
Bayesian Computation in Deep Learning Wenlong Chen Bolian Li Ruqi Zhang Yingzhen Li BDL 75 0 0 25 Feb 2025
Density Regression and Uncertainty Quantification with Bayesian Deep Noise Neural Networks Daiwei Zhang Tianci Liu Jian Kang BDL UQCV 43 2 0 12 Jun 2022
Approximate Inference via Clustering Qianqian Song 36 0 0 28 Nov 2021
Uncertainty quantification in non-rigid image registration via stochastic gradient Markov chain Monte Carlo Daniel Grzech Mohammad Farid Azampour Huaqi Qiu Ben Glocker Bernhard Kainz Loic Le Folgoc MedIm 19 2 0 25 Oct 2021
Is MC Dropout Bayesian? Loic Le Folgoc V. Baltatzis S. Desai A. Devaraj S. Ellis O. M. Manzanera A. Nair Huaqi Qiu Julia A. Schnabel Ben Glocker BDL OOD UQCV 30 39 0 08 Oct 2021
Disentangling the Roles of Curation, Data-Augmentation and the Prior in the Cold Posterior Effect Lorenzo Noci Kevin Roth Gregor Bachmann Sebastian Nowozin Thomas Hofmann CML 30 23 0 11 Jun 2021
A Survey on Large-scale Machine Learning Meng Wang Weijie Fu Xiangnan He Shijie Hao Xindong Wu 25 110 0 10 Aug 2020
Powering One-shot Topological NAS with Stabilized Share-parameter Proxy Ronghao Guo Chen Lin Chuming Li Keyu Tian Ming Sun Lu Sheng Junjie Yan BDL 34 17 0 21 May 2020
Stochastic Gradient Hamiltonian Monte Carlo for Non-Convex Learning Huy N. Chau M. Rásonyi 43 10 0 25 Mar 2019
Meta-Learning for Stochastic Gradient MCMC Wenbo Gong Yingzhen Li José Miguel Hernández-Lobato BDL 38 44 0 12 Jun 2018
Bayesian Pose Graph Optimization via Bingham Distributions and Tempered Geodesic MCMC Tolga Birdal Umut Simsekli M. Eken Slobodan Ilic 26 38 0 31 May 2018
Deep Rewiring: Training very sparse deep networks G. Bellec David Kappel Wolfgang Maass Robert Legenstein BDL 29 275 0 14 Nov 2017
Continuous-Time Flows for Efficient Inference and Density Estimation Changyou Chen Chunyuan Li Liquan Chen Wenlin Wang Yunchen Pu Lawrence Carin TPM 48 57 0 04 Sep 2017
Mini-batch Tempered MCMC Dangna Li W. Wong 29 5 0 31 Jul 2017
Fractional Langevin Monte Carlo: Exploring Lévy Driven Stochastic Differential Equations for Markov Chain Monte Carlo Umut Simsekli 35 45 0 12 Jun 2017
Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks Nanyang Ye Zhanxing Zhu Rafał K. Mantiuk 21 20 0 13 Mar 2017
Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling Zhe Gan Chunyuan Li Changyou Chen Yunchen Pu Qinliang Su Lawrence Carin BDL UQCV 55 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
Predictive Coarse-Graining M. Schöberl N. Zabaras P. Koutsourelakis 30 34 0 26 May 2016
Adding Gradient Noise Improves Learning for Very Deep Networks Arvind Neelakantan Luke Vilnis Quoc V. Le Ilya Sutskever Lukasz Kaiser Karol Kurach James Martens AI4CE ODL 27 541 0 21 Nov 2015