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Stochastic Gradient Descent as Approximate Bayesian Inference

13 April 2017

Matthew D. Hoffman

Papers citing "Stochastic Gradient Descent as Approximate Bayesian Inference"

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Title
Robust Simulation-Based Inference in Cosmology with Bayesian Neural Networks Pablo Lemos M. Cranmer Muntazir M. Abidi C. Hahn Michael Eickenberg E. Massara David Yallup S. Ho 38 24 0 18 Jul 2022
Implicit Regularization or Implicit Conditioning? Exact Risk Trajectories of SGD in High Dimensions Courtney Paquette Elliot Paquette Ben Adlam Jeffrey Pennington 63 14 0 15 Jun 2022
Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger Zhiqi Bu Yu Wang Sheng Zha George Karypis 132 72 0 14 Jun 2022
Density Regression and Uncertainty Quantification with Bayesian Deep Noise Neural Networks Daiwei Zhang Tianci Liu Jian Kang BDL UQCV 69 3 0 12 Jun 2022
Trajectory-dependent Generalization Bounds for Deep Neural Networks via Fractional Brownian Motion Chengli Tan Jiang Zhang Junmin Liu 78 1 0 09 Jun 2022
High-dimensional limit theorems for SGD: Effective dynamics and critical scaling Gerard Ben Arous Reza Gheissari Aukosh Jagannath 131 59 0 08 Jun 2022
Feature Space Particle Inference for Neural Network Ensembles Shingo Yashima Teppei Suzuki Kohta Ishikawa Ikuro Sato Rei Kawakami BDL 66 11 0 02 Jun 2022
Trainable Weight Averaging: Accelerating Training and Improving Generalization Tao Li Zhehao Huang Yingwen Wu Zhengbao He Qinghua Tao Xiaolin Huang Chih-Jen Lin MoMe 102 3 0 26 May 2022
NeuralEF: Deconstructing Kernels by Deep Neural Networks Zhijie Deng Jiaxin Shi Jun Zhu 134 19 0 30 Apr 2022
Neuronal diversity can improve machine learning for physics and beyond A. Choudhary Anil Radhakrishnan J. Lindner S. Sinha W. Ditto AI4CE 26 4 0 09 Apr 2022
Balanced Multimodal Learning via On-the-fly Gradient Modulation Xiaokang Peng Yake Wei Andong Deng Dong Wang Di Hu 103 215 0 29 Mar 2022
Gradient flows and randomised thresholding: sparse inversion and classification J. Latz 42 2 0 22 Mar 2022
Deep Bayesian ICP Covariance Estimation Andrea de Maio S. Lacroix 3DPC 35 8 0 23 Feb 2022
Interacting Contour Stochastic Gradient Langevin Dynamics Wei Deng Siqi Liang Botao Hao Guang Lin F. Liang BDL 79 10 0 20 Feb 2022
Fast online inference for nonlinear contextual bandit based on Generative Adversarial Network Yun-Da Tsai Shou-De Lin 80 5 0 17 Feb 2022
Hybridizing Physical and Data-driven Prediction Methods for Physicochemical Properties Fabian Jirasek Robert Bamler Stephan Mandt AI4CE 35 16 0 17 Feb 2022
PFGE: Parsimonious Fast Geometric Ensembling of DNNs Hao Guo Jiyong Jin B. Liu FedML 72 1 0 14 Feb 2022
A heteroencoder architecture for prediction of failure locations in porous metals using variational inference Wyatt Bridgman Xiaoxuan Zhang G. Teichert M. Khalil K. Garikipati Reese E. Jones UQCV AI4CE 67 5 0 31 Jan 2022
On the Power-Law Hessian Spectrums in Deep Learning Zeke Xie Qian-Yuan Tang Yunfeng Cai Mingming Sun P. Li ODL 99 10 0 31 Jan 2022
Separation of Scales and a Thermodynamic Description of Feature Learning in Some CNNs Inbar Seroussi Gadi Naveh Zohar Ringel 100 55 0 31 Dec 2021
Spatial-Temporal-Fusion BNN: Variational Bayesian Feature Layer Shiye Lei Zhuozhuo Tu Leszek Rutkowski Feng Zhou Li Shen Fengxiang He Dacheng Tao BDL 75 2 0 12 Dec 2021
A Continuous-time Stochastic Gradient Descent Method for Continuous Data Kexin Jin J. Latz Chenguang Liu Carola-Bibiane Schönlieb 87 9 0 07 Dec 2021
A generalization gap estimation for overparameterized models via the Langevin functional variance Akifumi Okuno Keisuke Yano 102 2 0 07 Dec 2021
Multi-scale Feature Learning Dynamics: Insights for Double Descent Mohammad Pezeshki Amartya Mitra Yoshua Bengio Guillaume Lajoie 105 27 0 06 Dec 2021
On Large Batch Training and Sharp Minima: A Fokker-Planck Perspective Xiaowu Dai Yuhua Zhu 42 4 0 02 Dec 2021
A Survey on Epistemic (Model) Uncertainty in Supervised Learning: Recent Advances and Applications Xinlei Zhou Han Liu Farhad Pourpanah T. Zeng Xizhao Wang UQCV UD 124 61 0 03 Nov 2021
Does Momentum Help? A Sample Complexity Analysis Swetha Ganesh Rohan Deb Gugan Thoppe A. Budhiraja 52 2 0 29 Oct 2021
Optimizing Information-theoretical Generalization Bounds via Anisotropic Noise in SGLD Bohan Wang Huishuai Zhang Jieyu Zhang Qi Meng Wei Chen Tie-Yan Liu 22 1 0 26 Oct 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 40 2 0 25 Oct 2021
Training Deep Neural Networks with Adaptive Momentum Inspired by the Quadratic Optimization Tao Sun Huaming Ling Zuoqiang Shi Dongsheng Li Bao Wang ODL 65 13 0 18 Oct 2021
Imitating Deep Learning Dynamics via Locally Elastic Stochastic Differential Equations Jiayao Zhang Hua Wang Weijie J. Su 96 8 0 11 Oct 2021
Batch size-invariance for policy optimization Jacob Hilton K. Cobbe John Schulman 120 14 0 01 Oct 2021
Revisiting the Characteristics of Stochastic Gradient Noise and Dynamics Yixin Wu Rui Luo Chen Zhang Jun Wang Yaodong Yang 98 7 0 20 Sep 2021
Assessments of epistemic uncertainty using Gaussian stochastic weight averaging for fluid-flow regression Masaki Morimoto Kai Fukami R. Maulik Ricardo Vinuesa K. Fukagata UQCV 84 31 0 16 Sep 2021
Mixing between the Cross Entropy and the Expectation Loss Terms Barak Battash Lior Wolf Tamir Hazan UQCV 86 0 0 12 Sep 2021
Sqrt(d) Dimension Dependence of Langevin Monte Carlo Ruilin Li H. Zha Molei Tao 94 29 0 08 Sep 2021
Shift-Curvature, SGD, and Generalization Arwen V. Bradley C. Gomez-Uribe Manish Reddy Vuyyuru 62 3 0 21 Aug 2021
On Accelerating Distributed Convex Optimizations Kushal Chakrabarti Nirupam Gupta Nikhil Chopra 67 7 0 19 Aug 2021
SGD with a Constant Large Learning Rate Can Converge to Local Maxima Liu Ziyin Botao Li James B. Simon Masakuni Ueda 92 9 0 25 Jul 2021
Differentiable Annealed Importance Sampling and the Perils of Gradient Noise Guodong Zhang Kyle Hsu Jianing Li Chelsea Finn Roger C. Grosse 85 40 0 21 Jul 2021
Structured Stochastic Gradient MCMC Antonios Alexos Alex Boyd Stephan Mandt BDL 76 13 0 19 Jul 2021
Epistemic Neural Networks Ian Osband Zheng Wen M. Asghari Vikranth Dwaracherla M. Ibrahimi Xiyuan Lu Benjamin Van Roy UQCV BDL 134 109 0 19 Jul 2021
The Bayesian Learning Rule Mohammad Emtiyaz Khan Håvard Rue BDL 159 83 0 09 Jul 2021
Imaging dynamics beneath turbid media via parallelized single-photon detection Shiqi Xu Xi Yang Wenhui Liu J. Jonsson Ruobing Qian ... Lucas Kreiss Qionghai Dai Haoqian Wang E. Berrocal R. Horstmeyer 38 14 0 03 Jul 2021
Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks Suryanarayana Maddu D. Sturm Christian L. Müller I. Sbalzarini AI4CE 87 83 0 02 Jul 2021
Revisiting the Effects of Stochasticity for Hamiltonian Samplers Giulio Franzese Dimitrios Milios Maurizio Filippone Pietro Michiardi 39 3 0 30 Jun 2021
Implicit Gradient Alignment in Distributed and Federated Learning Yatin Dandi Luis Barba Martin Jaggi FedML 131 35 0 25 Jun 2021
Repulsive Deep Ensembles are Bayesian Francesco DÁngelo Vincent Fortuin UQCV BDL 125 101 0 22 Jun 2021
Deep Learning Through the Lens of Example Difficulty R. Baldock Hartmut Maennel Behnam Neyshabur 91 161 0 17 Jun 2021
On Linear Stability of SGD and Input-Smoothness of Neural Networks Chao Ma Lexing Ying MLT 66 44 0 27 May 2021