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Noisy Natural Gradient as Variational Inference

6 December 2017

Papers citing "Noisy Natural Gradient as Variational Inference"

50 / 104 papers shown

Title
Dissecting Hessian: Understanding Common Structure of Hessian in Neural Networks Yikai Wu Xingyu Zhu Chenwei Wu Annie Wang Rong Ge 118 45 0 08 Oct 2020
Task Agnostic Continual Learning Using Online Variational Bayes with Fixed-Point Updates Chen Zeno Itay Golan Elad Hoffer Daniel Soudry OOD FedML 90 47 0 01 Oct 2020
Action and Perception as Divergence Minimization Danijar Hafner Pedro A. Ortega Jimmy Ba Thomas Parr Karl J. Friston N. Heess 91 53 0 03 Sep 2020
SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates Lingkai Kong Jimeng Sun Chao Zhang UQCV 107 108 0 24 Aug 2020
A statistical theory of cold posteriors in deep neural networks Laurence Aitchison UQCV BDL 90 70 0 13 Aug 2020
Stochastic Bayesian Neural Networks Abhinav Sagar BDL UQCV 48 0 0 12 Aug 2020
Descending through a Crowded Valley - Benchmarking Deep Learning Optimizers Robin M. Schmidt Frank Schneider Philipp Hennig ODL 217 168 0 03 Jul 2020
Estimating Model Uncertainty of Neural Networks in Sparse Information Form Jongseo Lee Matthias Humt Jianxiang Feng Rudolph Triebel BDL UQCV 103 47 0 20 Jun 2020
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes Sebastian W. Ober Laurence Aitchison BDL 116 60 0 17 May 2020
Prior choice affects ability of Bayesian neural networks to identify unknowns D. Silvestro Tobias Andermann UQCV BDL 64 23 0 11 May 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 90 290 0 24 Feb 2020
Handling the Positive-Definite Constraint in the Bayesian Learning Rule Wu Lin Mark Schmidt Mohammad Emtiyaz Khan BDL 181 36 0 24 Feb 2020
Being Bayesian about Categorical Probability Taejong Joo U. Chung Minji Seo UQCV BDL 97 61 0 19 Feb 2020
Scalable and Practical Natural Gradient for Large-Scale Deep Learning Kazuki Osawa Yohei Tsuji Yuichiro Ueno Akira Naruse Chuan-Sheng Foo Rio Yokota 85 37 0 13 Feb 2020
Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights Theofanis Karaletsos T. Bui BDL 107 24 0 10 Feb 2020
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks J. Swiatkowski Kevin Roth Bastiaan S. Veeling Linh-Tam Tran Joshua V. Dillon Jasper Snoek Stephan Mandt Tim Salimans Rodolphe Jenatton Sebastian Nowozin BDL 76 47 0 07 Feb 2020
Measuring Uncertainty through Bayesian Learning of Deep Neural Network Structure Zhijie Deng Yucen Luo Jun Zhu Bo Zhang UQCV BDL 43 2 0 22 Nov 2019
Bayesian interpretation of SGD as Ito process Soma Yokoi Issei Sato 43 5 0 20 Nov 2019
Optimizing Millions of Hyperparameters by Implicit Differentiation Jonathan Lorraine Paul Vicol David Duvenaud DD 139 417 0 06 Nov 2019
Challenges in Markov chain Monte Carlo for Bayesian neural networks Theodore Papamarkou Jacob D. Hinkle M. T. Young D. Womble BDL 131 51 0 15 Oct 2019
Dissecting Non-Vacuous Generalization Bounds based on the Mean-Field Approximation Konstantinos Pitas 73 8 0 06 Sep 2019
Sampling-free Epistemic Uncertainty Estimation Using Approximated Variance Propagation Janis Postels Francesco Ferroni Huseyin Coskun Nassir Navab Federico Tombari UQCV UD PER BDL 147 140 0 01 Aug 2019
The Functional Neural Process Christos Louizos Xiahan Shi Klamer Schutte Max Welling BDL 82 77 0 19 Jun 2019
Stochastic Neural Network with Kronecker Flow Chin-Wei Huang Ahmed Touati Pascal Vincent Gintare Karolina Dziugaite Alexandre Lacoste Aaron Courville BDL 67 8 0 10 Jun 2019
Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations Wu Lin Mohammad Emtiyaz Khan Mark Schmidt BDL 99 71 0 07 Jun 2019
Practical Deep Learning with Bayesian Principles Kazuki Osawa S. Swaroop Anirudh Jain Runa Eschenhagen Richard Turner Rio Yokota Mohammad Emtiyaz Khan BDL UQCV 167 247 0 06 Jun 2019
Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision Fredrik K. Gustafsson Martin Danelljan Thomas B. Schon OOD UQCV BDL 82 302 0 04 Jun 2019
Limitations of the Empirical Fisher Approximation for Natural Gradient Descent Frederik Kunstner Lukas Balles Philipp Hennig 101 219 0 29 May 2019
Walsh-Hadamard Variational Inference for Bayesian Deep Learning Simone Rossi Sébastien Marmin Maurizio Filippone BDL 101 16 0 27 May 2019
Fast Convergence of Natural Gradient Descent for Overparameterized Neural Networks Guodong Zhang James Martens Roger C. Grosse ODL 113 126 0 27 May 2019
EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis Chaoqi Wang Roger C. Grosse Sanja Fidler Guodong Zhang 80 124 0 15 May 2019
Generalized Variational Inference: Three arguments for deriving new Posteriors Jeremias Knoblauch Jack Jewson Theodoros Damoulas DRL BDL 109 106 0 03 Apr 2019
Functional Variational Bayesian Neural Networks Shengyang Sun Guodong Zhang Jiaxin Shi Roger C. Grosse BDL 71 240 0 14 Mar 2019
Fisher-Bures Adversary Graph Convolutional Networks Ke Sun Piotr Koniusz Zhen Wang GNN 60 34 0 11 Mar 2019
Function Space Particle Optimization for Bayesian Neural Networks Ziyu Wang Zhaolin Ren Jun Zhu Bo Zhang BDL 73 65 0 26 Feb 2019
An Empirical Study of Large-Batch Stochastic Gradient Descent with Structured Covariance Noise Yeming Wen Kevin Luk Maxime Gazeau Guodong Zhang Harris Chan Jimmy Ba ODL 73 22 0 21 Feb 2019
Evaluating model calibration in classification Juozas Vaicenavicius David Widmann Carl R. Andersson Fredrik Lindsten Jacob Roll Thomas B. Schon UQCV 182 200 0 19 Feb 2019
Manifold Optimization Assisted Gaussian Variational Approximation Bingxin Zhou Junbin Gao Minh-Ngoc Tran Richard Gerlach 67 6 0 11 Feb 2019
Radial and Directional Posteriors for Bayesian Neural Networks Changyong Oh Kamil Adamczewski Mijung Park BDL 115 20 0 07 Feb 2019
A Simple Baseline for Bayesian Uncertainty in Deep Learning Wesley J. Maddox T. Garipov Pavel Izmailov Dmitry Vetrov A. Wilson BDL UQCV 150 810 0 07 Feb 2019
Predictive Uncertainty Quantification with Compound Density Networks Agustinus Kristiadi Sina Daubener Asja Fischer BDL UQCV 68 17 0 04 Feb 2019
Bayesian Layers: A Module for Neural Network Uncertainty Dustin Tran Michael W. Dusenberry Mark van der Wilk Danijar Hafner UQCV BDL 131 124 0 10 Dec 2018
Eigenvalue Corrected Noisy Natural Gradient Juhan Bae Guodong Zhang Roger C. Grosse 92 18 0 30 Nov 2018
Large-Scale Distributed Second-Order Optimization Using Kronecker-Factored Approximate Curvature for Deep Convolutional Neural Networks Kazuki Osawa Yohei Tsuji Yuichiro Ueno Akira Naruse Rio Yokota Satoshi Matsuoka ODL 107 95 0 29 Nov 2018
SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient Aaron Mishkin Frederik Kunstner Didrik Nielsen Mark Schmidt Mohammad Emtiyaz Khan BDL UQCV 90 60 0 11 Nov 2018
Three Mechanisms of Weight Decay Regularization Guodong Zhang Chaoqi Wang Bowen Xu Roger C. Grosse 75 259 0 29 Oct 2018
Good Initializations of Variational Bayes for Deep Models Simone Rossi Pietro Michiardi Maurizio Filippone BDL 130 22 0 18 Oct 2018
Inhibited Softmax for Uncertainty Estimation in Neural Networks Marcin Mo.zejko Mateusz Susik Rafal Karczewski UQCV 75 29 0 03 Oct 2018
An elementary introduction to information geometry Frank Nielsen 3DGS 54 223 0 17 Aug 2018
Bayesian filtering unifies adaptive and non-adaptive neural network optimization methods Laurence Aitchison ODL 125 21 0 19 Jul 2018