Uncertainty Calibration in Bayesian Neural Networks via Distance-Aware Priors

17 July 2022

Papers citing "Uncertainty Calibration in Bayesian Neural Networks via Distance-Aware Priors"

33 / 33 papers shown

Title
GETS: Ensemble Temperature Scaling for Calibration in Graph Neural Networks Dingyi Zhuang Chonghe Jiang Yunhan Zheng Shenhao Wang Jinhua Zhao UQCV 109 0 0 12 Oct 2024
On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification Sanyam Kapoor Wesley J. Maddox Pavel Izmailov A. Wilson BDL UD 79 51 0 30 Mar 2022
Laplace Redux -- Effortless Bayesian Deep Learning Erik A. Daxberger Agustinus Kristiadi Alexander Immer Runa Eschenhagen Matthias Bauer Philipp Hennig BDL UQCV 221 315 0 28 Jun 2021
Dangers of Bayesian Model Averaging under Covariate Shift Pavel Izmailov Patrick K. Nicholson Sanae Lotfi A. Wilson OOD UQCV BDL 127 46 0 22 Jun 2021
What Are Bayesian Neural Network Posteriors Really Like? Pavel Izmailov Sharad Vikram Matthew D. Hoffman A. Wilson UQCV BDL 74 387 0 29 Apr 2021
On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty Joost R. van Amersfoort Lewis Smith Andrew Jesson Oscar Key Y. Gal UQCV 77 104 0 22 Feb 2021
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness Jeremiah Zhe Liu Zi Lin Shreyas Padhy Dustin Tran Tania Bedrax-Weiss Balaji Lakshminarayanan UQCV BDL 233 451 0 17 Jun 2020
Bayesian Deep Learning and a Probabilistic Perspective of Generalization A. Wilson Pavel Izmailov UQCV BDL OOD 115 656 0 20 Feb 2020
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods Eyke Hüllermeier Willem Waegeman PER UD 249 1,427 0 21 Oct 2019
Ín-Between' Uncertainty in Bayesian Neural Networks Andrew Y. K. Foong Yingzhen Li José Miguel Hernández-Lobato Richard Turner BDL UQCV 71 121 0 27 Jun 2019
Quality of Uncertainty Quantification for Bayesian Neural Network Inference Jiayu Yao Weiwei Pan S. Ghosh Finale Doshi-Velez UQCV BDL 181 113 0 24 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 151 247 0 06 Jun 2019
Conformal calibrators V. Vovk Ivan Petej Paolo Toccaceli A. Gammerman 235 26 0 18 Feb 2019
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning Ruqi Zhang Chunyuan Li Jianyi Zhang Changyou Chen A. Wilson BDL 74 279 0 11 Feb 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
Accurate Uncertainties for Deep Learning Using Calibrated Regression Volodymyr Kuleshov Nathan Fenner Stefano Ermon BDL UQCV 206 636 0 01 Jul 2018
Predictive Uncertainty Estimation via Prior Networks A. Malinin Mark Gales UD BDL EDL UQCV PER 197 923 0 28 Feb 2018
Spectral Normalization for Generative Adversarial Networks Takeru Miyato Toshiki Kataoka Masanori Koyama Yuichi Yoshida ODL 164 4,445 0 16 Feb 2018
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 285 8,926 0 25 Aug 2017
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 299 5,871 0 14 Jun 2017
Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks Shiyu Liang Yixuan Li R. Srikant UQCV OODD 171 2,082 0 08 Jun 2017
Improved Training of Wasserstein GANs Ishaan Gulrajani Faruk Ahmed Martín Arjovsky Vincent Dumoulin Aaron Courville GAN 227 9,564 0 31 Mar 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 362 4,721 0 15 Mar 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 842 5,847 0 05 Dec 2016
Stochastic Variational Deep Kernel Learning A. Wilson Zhiting Hu Ruslan Salakhutdinov Eric Xing BDL 117 268 0 01 Nov 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 353 8,002 0 23 May 2016
Variational Inference: A Review for Statisticians David M. Blei A. Kucukelbir Jon D. McAuliffe BDL 298 4,812 0 04 Jan 2016
Deep Kernel Learning A. Wilson Zhiting Hu Ruslan Salakhutdinov Eric Xing BDL 256 889 0 06 Nov 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 860 9,353 0 06 Jun 2015
Variational Inference with Normalizing Flows Danilo Jimenez Rezende S. Mohamed DRL BDL 322 4,197 0 21 May 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.1K 150,364 0 22 Dec 2014
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 455 16,922 0 20 Dec 2013
MCMC using Hamiltonian dynamics Radford M. Neal 293 3,282 0 09 Jun 2012