On Calibration of Modern Neural Networks

14 June 2017

Papers citing "On Calibration of Modern Neural Networks"

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Title
Distance-Based Learning from Errors for Confidence Calibration Chen Xing Sercan Ö. Arik Zizhao Zhang Tomas Pfister FedML 23 39 0 03 Dec 2019
On the Validity of Bayesian Neural Networks for Uncertainty Estimation John Mitros Brian Mac Namee UQCV BDL 10 29 0 03 Dec 2019
The Group Loss for Deep Metric Learning Ismail Elezi Sebastiano Vascon Alessandro Torcinovich Marcello Pelillo Laura Leal-Taixe 19 50 0 01 Dec 2019
Confidence Calibration and Predictive Uncertainty Estimation for Deep Medical Image Segmentation Alireza Mehrtash W. Wells C. Tempany Purang Abolmaesumi Tina Kapur OOD FedML UQCV 24 265 0 29 Nov 2019
Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models Tong Che Xiaofeng Liu Site Li Yubin Ge Ruixiang Zhang Caiming Xiong Yoshua Bengio 38 52 0 18 Nov 2019
Disentangle, align and fuse for multimodal and semi-supervised image segmentation A. Chartsias G. Papanastasiou Chengjia Wang S. Semple D. Newby R. Dharmakumar Sotirios A. Tsaftaris 24 13 0 11 Nov 2019
Knowledge Distillation for Incremental Learning in Semantic Segmentation Umberto Michieli Pietro Zanuttigh CLL VLM 28 98 0 08 Nov 2019
Confident Learning: Estimating Uncertainty in Dataset Labels Curtis G. Northcutt Lu Jiang Isaac L. Chuang NoLa 43 674 0 31 Oct 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 31 370 0 28 Oct 2019
Detecting Out-of-Distribution Inputs in Deep Neural Networks Using an Early-Layer Output Vahdat Abdelzad Krzysztof Czarnecki Rick Salay Taylor Denouden Sachin Vernekar Buu Phan OODD 24 45 0 23 Oct 2019
Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction Ajay Jain Sergio Casas Renjie Liao Yuwen Xiong Song Feng Sean Segal R. Urtasun 156 73 0 17 Oct 2019
Consistency-based Semi-supervised Active Learning: Towards Minimizing Labeling Cost M. Gao Zizhao Zhang Guo-Ding Yu Sercan Ö. Arik L. Davis Tomas Pfister 168 196 0 16 Oct 2019
Out-of-distribution Detection in Classifiers via Generation Sachin Vernekar Ashish Gaurav Vahdat Abdelzad Taylor Denouden Rick Salay Krzysztof Czarnecki OODD 27 83 0 09 Oct 2019
Adversarial Examples for Cost-Sensitive Classifiers Mahdi Akbari Zarkesh A. Lohn Ali Movaghar SILM AAML 24 3 0 04 Oct 2019
On the Efficacy of Knowledge Distillation Ligang He Rui Mao 42 600 0 03 Oct 2019
Addressing Failure Prediction by Learning Model Confidence Charles Corbière Nicolas Thome Avner Bar-Hen Matthieu Cord P. Pérez 33 283 0 01 Oct 2019
Test-Time Training with Self-Supervision for Generalization under Distribution Shifts Yu Sun Xiaolong Wang Zhuang Liu John Miller Alexei A. Efros Moritz Hardt TTA OOD 27 92 0 29 Sep 2019
Training-Free Uncertainty Estimation for Dense Regression: Sensitivity as a Surrogate Lu Mi Hao Wang Yonglong Tian Hao He Nir Shavit UQCV 21 30 0 28 Sep 2019
Towards neural networks that provably know when they don't know Alexander Meinke Matthias Hein OODD 33 139 0 26 Sep 2019
Verified Uncertainty Calibration Ananya Kumar Percy Liang Tengyu Ma 24 346 0 23 Sep 2019
Sampling Bias in Deep Active Classification: An Empirical Study Ameya Prabhu Charles Dognin M. Singh 19 64 0 20 Sep 2019
Risk-Aware Planning by Confidence Estimation using Deep Learning-Based Perception Maymoonah Toubeh Pratap Tokekar UQCV 17 4 0 13 Sep 2019
Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors Jayaraman J. Thiagarajan Bindya Venkatesh P. Sattigeri P. Bremer UQCV 25 31 0 09 Sep 2019
Out-of-domain Detection for Natural Language Understanding in Dialog Systems Yinhe Zheng Guanyi Chen Minlie Huang 28 121 0 09 Sep 2019
Bin-wise Temperature Scaling (BTS): Improvement in Confidence Calibration Performance through Simple Scaling Techniques Byeongmoon Ji Hyemin Jung Jihyeun Yoon Kyungyul Kim Younghak Shin UQCV 24 24 0 30 Aug 2019
Confidence Regularized Self-Training Yang Zou Zhiding Yu Xiaofeng Liu B. Kumar Jinsong Wang 233 790 0 26 Aug 2019
Density estimation in representation space to predict model uncertainty Tiago Ramalho M. Corbalan UQCV BDL 16 38 0 20 Aug 2019
Regularizing CNN Transfer Learning with Randomised Regression Yang Zhong A. Maki 24 13 0 16 Aug 2019
Entropic Out-of-Distribution Detection David Macêdo T. I. Ren Cleber Zanchettin Adriano Oliveira Teresa B Ludermir OODD UQCV 25 32 0 15 Aug 2019
Dynamic Scale Inference by Entropy Minimization Dequan Wang Evan Shelhamer Bruno A. Olshausen Trevor Darrell 27 7 0 08 Aug 2019
Deep Learning for Detecting Building Defects Using Convolutional Neural Networks H. Perez J. Tah Amir H. Mosavi 15 194 0 06 Aug 2019
Uncertainty in Model-Agnostic Meta-Learning using Variational Inference Cuong C. Nguyen Thanh-Toan Do G. Carneiro OOD BDL UQCV 19 54 0 27 Jul 2019
Subspace Inference for Bayesian Deep Learning Pavel Izmailov Wesley J. Maddox Polina Kirichenko T. Garipov Dmitry Vetrov A. Wilson UQCV BDL 38 142 0 17 Jul 2019
Natural Adversarial Examples Dan Hendrycks Kevin Zhao Steven Basart Jacob Steinhardt D. Song OODD 92 1,426 0 16 Jul 2019
Assessing Reliability and Challenges of Uncertainty Estimations for Medical Image Segmentation Alain Jungo M. Reyes UQCV 30 134 0 07 Jul 2019
Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting Aditya Grover Jiaming Song Alekh Agarwal Kenneth Tran Ashish Kapoor Eric Horvitz Stefano Ermon 26 123 0 23 Jun 2019
Efficient Evaluation-Time Uncertainty Estimation by Improved Distillation Erik Englesson Hossein Azizpour UQCV 19 8 0 12 Jun 2019
Non-Parametric Calibration for Classification Jonathan Wenger Hedvig Kjellström Rudolph Triebel UQCV 45 79 0 12 Jun 2019
Analyzing the Role of Model Uncertainty for Electronic Health Records Michael W. Dusenberry Dustin Tran Edward Choi Jonas Kemp Jeremy Nixon Ghassen Jerfel Katherine A. Heller Andrew M. Dai 18 117 0 10 Jun 2019
Learning Adaptive Classifiers Synthesis for Generalized Few-Shot Learning Han-Jia Ye Hexiang Hu De-Chuan Zhan 25 59 0 07 Jun 2019
Likelihood Ratios for Out-of-Distribution Detection Jie Jessie Ren Peter J. Liu Emily Fertig Jasper Snoek Ryan Poplin M. DePristo Joshua V. Dillon Balaji Lakshminarayanan OODD 50 716 0 07 Jun 2019
When Does Label Smoothing Help? Rafael Müller Simon Kornblith Geoffrey E. Hinton UQCV 61 1,912 0 06 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 29 1,658 0 06 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 56 240 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 21 13 0 30 May 2019
Evaluating and Calibrating Uncertainty Prediction in Regression Tasks Dan Levi Liran Gispan Niv Giladi Ethan Fetaya UQCV 16 142 0 28 May 2019
Privacy Risks of Securing Machine Learning Models against Adversarial Examples Liwei Song Reza Shokri Prateek Mittal SILM MIACV AAML 6 235 0 24 May 2019
Ensemble Model Patching: A Parameter-Efficient Variational Bayesian Neural Network Oscar Chang Yuling Yao David Williams-King Hod Lipson BDL UQCV 32 8 0 23 May 2019
Detecting Adversarial Examples and Other Misclassifications in Neural Networks by Introspection Jonathan Aigrain Marcin Detyniecki AAML 27 30 0 22 May 2019
Distribution Calibration for Regression Hao Song Tom Diethe Meelis Kull Peter A. Flach UQCV 33 108 0 15 May 2019