Improving model calibration with accuracy versus uncertainty optimization

14 December 2020

Papers citing "Improving model calibration with accuracy versus uncertainty optimization"

36 / 36 papers shown

Title
Beyond One-Hot Labels: Semantic Mixing for Model Calibration Haoyang Luo Linwei Tao Minjing Dong Chang Xu 72 0 0 18 Apr 2025
Uncertainty Weighted Gradients for Model Calibration Jinxu Lin Linwei Tao Minjing Dong Chang Xu UQCV 65 0 0 26 Mar 2025
Calibrating Bayesian Learning via Regularization, Confidence Minimization, and Selective Inference Jiayi Huang Sangwoo Park Osvaldo Simeone 134 2 0 03 Jan 2025
Optimizing Calibration by Gaining Aware of Prediction Correctness Yuchi Liu Lei Wang Yuli Zou James Zou Liang Zheng UQCV 61 2 0 19 Apr 2024
An Empirical Study of Pre-trained Model Selection for Out-of-Distribution Generalization and Calibration Hiroki Naganuma Ryuichiro Hataya Kotaro Yoshida Ioannis Mitliagkas OODD 135 3 0 17 Jul 2023
Calibrating Deep Neural Networks using Focal Loss Jishnu Mukhoti Viveka Kulharia Amartya Sanyal Stuart Golodetz Philip Torr P. Dokania UQCV 69 454 0 21 Feb 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 211 42,038 0 03 Dec 2019
Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration Meelis Kull Miquel Perelló Nieto Markus Kängsepp Telmo de Menezes e Silva Filho Hao Song Peter A. Flach UQCV 53 378 0 28 Oct 2019
Well-calibrated Model Uncertainty with Temperature Scaling for Dropout Variational Inference M. Laves Sontje Ihler Karl-Philipp Kortmann T. Ortmaier UQCV 27 55 0 30 Sep 2019
Verified Uncertainty Calibration Ananya Kumar Percy Liang Tengyu Ma 106 352 0 23 Sep 2019
Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning Sebastian Farquhar Michael A. Osborne Y. Gal UQCV BDL 36 56 0 01 Jul 2019
Ín-Between' Uncertainty in Bayesian Neural Networks Andrew Y. K. Foong Yingzhen Li José Miguel Hernández-Lobato Richard Turner BDL UQCV 46 117 0 27 Jun 2019
Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes R. Krishnan Mahesh Subedar Omesh Tickoo BDL 35 47 0 12 Jun 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 135 1,677 0 06 Jun 2019
Modeling Uncertainty by Learning a Hierarchy of Deep Neural Connections R. Y. Rohekar Yaniv Gurwicz Shami Nisimov Gal Novik BDL UQCV 97 13 0 30 May 2019
On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks S. Thulasidasan Gopinath Chennupati J. Bilmes Tanmoy Bhattacharya S. Michalak UQCV 57 535 0 27 May 2019
The Fishyscapes Benchmark: Measuring Blind Spots in Semantic Segmentation Hermann Blum Paul-Edouard Sarlin Juan I. Nieto Roland Siegwart Cesar Cadena UQCV 23 157 0 05 Apr 2019
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations Dan Hendrycks Thomas G. Dietterich OOD VLM 96 3,399 0 28 Mar 2019
A Simple Baseline for Bayesian Uncertainty in Deep Learning Wesley J. Maddox T. Garipov Pavel Izmailov Dmitry Vetrov A. Wilson BDL UQCV 71 801 0 07 Feb 2019
Evaluating Bayesian Deep Learning Methods for Semantic Segmentation Jishnu Mukhoti Y. Gal UQCV BDL 55 221 0 30 Nov 2018
Strike (with) a Pose: Neural Networks Are Easily Fooled by Strange Poses of Familiar Objects Michael A. Alcorn Melvin Johnson Zhitao Gong Chengfei Wang Long Mai Naveen Ari Stella Laurenzo 78 299 0 28 Nov 2018
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks Kimin Lee Kibok Lee Honglak Lee Jinwoo Shin OODD 108 2,024 0 10 Jul 2018
Accurate Uncertainties for Deep Learning Using Calibrated Regression Volodymyr Kuleshov Nathan Fenner Stefano Ermon BDL UQCV 131 626 0 01 Jul 2018
Loss-Calibrated Approximate Inference in Bayesian Neural Networks Adam D. Cobb Stephen J. Roberts Y. Gal BDL UQCV 42 43 0 10 May 2018
Understanding Measures of Uncertainty for Adversarial Example Detection Lewis Smith Y. Gal UQCV 75 361 0 22 Mar 2018
Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling C. Riquelme George Tucker Jasper Snoek BDL 55 365 0 26 Feb 2018
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 181 5,774 0 14 Jun 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 250 4,667 0 15 Mar 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 463 5,748 0 05 Dec 2016
Concrete Problems in AI Safety Dario Amodei C. Olah Jacob Steinhardt Paul Christiano John Schulman Dandelion Mané 143 2,349 0 21 Jun 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 1.2K 192,638 0 10 Dec 2015
On Wasserstein Two Sample Testing and Related Families of Nonparametric Tests Aaditya Ramdas Nicolas García Trillos Marco Cuturi 34 482 0 08 Sep 2015
Variational Dropout and the Local Reparameterization Trick Diederik P. Kingma Tim Salimans Max Welling BDL 144 1,500 0 08 Jun 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 439 9,233 0 06 Jun 2015
Stochastic Gradient Hamiltonian Monte Carlo Tianqi Chen E. Fox Carlos Guestrin BDL 62 902 0 17 Feb 2014
Bayesian Active Learning for Classification and Preference Learning N. Houlsby Ferenc Huszár Zoubin Ghahramani M. Lengyel 58 901 0 24 Dec 2011