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Mean-Field Approximation to Gaussian-Softmax Integral with Application to Uncertainty Estimation

13 June 2020

Papers citing "Mean-Field Approximation to Gaussian-Softmax Integral with Application to Uncertainty Estimation"

21 / 21 papers shown

Title
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 88 289 0 24 Feb 2020
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning Arsenii Ashukha Alexander Lyzhov Dmitry Molchanov Dmitry Vetrov UQCV FedML 84 320 0 15 Feb 2020
A Higher-Order Swiss Army Infinitesimal Jackknife Ryan Giordano Michael I. Jordan Tamara Broderick UQCV 44 30 0 28 Jul 2019
Natural Adversarial Examples Dan Hendrycks Kevin Zhao Steven Basart Jacob Steinhardt Basel Alomair OODD 230 1,484 0 16 Jul 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift Yaniv Ovadia Emily Fertig Jie Jessie Ren Zachary Nado D. Sculley Sebastian Nowozin Joshua V. Dillon Balaji Lakshminarayanan Jasper Snoek UQCV 185 1,705 0 06 Jun 2019
A Simple Baseline for Bayesian Uncertainty in Deep Learning Wesley J. Maddox T. Garipov Pavel Izmailov Dmitry Vetrov A. Wilson BDL UQCV 99 809 0 07 Feb 2019
The Relevance of Bayesian Layer Positioning to Model Uncertainty in Deep Bayesian Active Learning Jiaming Zeng Adam Lesnikowski J. Álvarez OOD UQCV BDL 62 28 0 29 Nov 2018
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks Kimin Lee Kibok Lee Honglak Lee Jinwoo Shin OODD 192 2,063 0 10 Jul 2018
Evidential Deep Learning to Quantify Classification Uncertainty Murat Sensoy Lance M. Kaplan M. Kandemir OOD UQCV EDL BDL 188 1,002 0 05 Jun 2018
Predictive Uncertainty Estimation via Prior Networks A. Malinin Mark Gales UD BDL EDL UQCV PER 197 923 0 28 Feb 2018
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 299 5,871 0 14 Jun 2017
Stochastic Gradient Descent as Approximate Bayesian Inference Stephan Mandt Matthew D. Hoffman David M. Blei BDL 67 599 0 13 Apr 2017
Snapshot Ensembles: Train 1, get M for free Gao Huang Yixuan Li Geoff Pleiss Zhuang Liu John E. Hopcroft Kilian Q. Weinberger OOD FedML UQCV 138 952 0 01 Apr 2017
Understanding Black-box Predictions via Influence Functions Pang Wei Koh Percy Liang TDI 219 2,910 0 14 Mar 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 842 5,841 0 05 Dec 2016
Statistical Inference for Model Parameters in Stochastic Gradient Descent Xi Chen Jason D. Lee Xin T. Tong Yichen Zhang 70 139 0 27 Oct 2016
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks Dan Hendrycks Kevin Gimpel UQCV 171 3,480 0 07 Oct 2016
Second-Order Stochastic Optimization for Machine Learning in Linear Time Naman Agarwal Brian Bullins Elad Hazan ODL 67 102 0 12 Feb 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 856 9,353 0 06 Jun 2015
Weight Uncertainty in Neural Networks Charles Blundell Julien Cornebise Koray Kavukcuoglu Daan Wierstra UQCV BDL 192 1,893 0 20 May 2015
Stochastic Gradient Hamiltonian Monte Carlo Tianqi Chen E. Fox Carlos Guestrin BDL 122 913 0 17 Feb 2014