On Calibration of Modern Neural Networks

14 June 2017

Papers citing "On Calibration of Modern Neural Networks"

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Title
OoDAnalyzer: Interactive Analysis of Out-of-Distribution Samples Changjian Chen Jun Yuan Yafeng Lu Yang Liu Hang Su Songtao Yuan Shixia Liu OODD 13 63 0 08 Feb 2020
Safety Concerns and Mitigation Approaches Regarding the Use of Deep Learning in Safety-Critical Perception Tasks Oliver Willers Sebastian Sudholt Shervin Raafatnia Stephanie Abrecht 20 80 0 22 Jan 2020
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference Timo Schick Hinrich Schütze 258 1,588 0 21 Jan 2020
Personalized Activity Recognition with Deep Triplet Embeddings D. Burns C. Whyne HAI 19 25 0 15 Jan 2020
Semi-Supervised Learning with Normalizing Flows Pavel Izmailov Polina Kirichenko Marc Finzi A. Wilson DRL BDL 25 111 0 30 Dec 2019
TRADI: Tracking deep neural network weight distributions for uncertainty estimation Gianni Franchi Andrei Bursuc Emanuel Aldea Séverine Dubuisson Isabelle Bloch UQCV 26 51 0 24 Dec 2019
Probability Calibration for Knowledge Graph Embedding Models Pedro Tabacof Luca Costabello 6 45 0 20 Dec 2019
On-manifold Adversarial Data Augmentation Improves Uncertainty Calibration Kanil Patel William H. Beluch Dan Zhang Michael Pfeiffer Bin Yang UQCV 19 30 0 16 Dec 2019
Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One Will Grathwohl Kuan-Chieh Jackson Wang J. Jacobsen David Duvenaud Mohammad Norouzi Kevin Swersky VLM 43 527 0 06 Dec 2019
Deep learning with noisy labels: exploring techniques and remedies in medical image analysis Davood Karimi Haoran Dou Simon K. Warfield Ali Gholipour NoLa 13 535 0 05 Dec 2019
Angular Visual Hardness Beidi Chen Weiyang Liu Zhiding Yu Jan Kautz Anshumali Shrivastava Animesh Garg Anima Anandkumar AAML 40 51 0 04 Dec 2019
Distance-Based Learning from Errors for Confidence Calibration Chen Xing Sercan Ö. Arik Zizhao Zhang Tomas Pfister FedML 21 39 0 03 Dec 2019
The Group Loss for Deep Metric Learning Ismail Elezi Sebastiano Vascon Alessandro Torcinovich Marcello Pelillo Laura Leal-Taixe 14 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 24 262 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 33 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 36 674 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 22 368 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 19 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 149 73 0 17 Oct 2019
Out-of-distribution Detection in Classifiers via Generation Sachin Vernekar Ashish Gaurav Vahdat Abdelzad Taylor Denouden Rick Salay Krzysztof Czarnecki OODD 19 83 0 09 Oct 2019
Adversarial Examples for Cost-Sensitive Classifiers Mahdi Akbari Zarkesh A. Lohn Ali Movaghar SILM AAML 22 3 0 04 Oct 2019
Addressing Failure Prediction by Learning Model Confidence Charles Corbière Nicolas Thome Avner Bar-Hen Matthieu Cord P. Pérez 27 281 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 91 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 29 0 28 Sep 2019
Towards neural networks that provably know when they don't know Alexander Meinke Matthias Hein OODD 22 139 0 26 Sep 2019
Verified Uncertainty Calibration Ananya Kumar Percy Liang Tengyu Ma 22 345 0 23 Sep 2019
Sampling Bias in Deep Active Classification: An Empirical Study Ameya Prabhu Charles Dognin M. Singh 11 64 0 20 Sep 2019
Risk-Aware Planning by Confidence Estimation using Deep Learning-Based Perception Maymoonah Toubeh Pratap Tokekar UQCV 9 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 17 31 0 09 Sep 2019
Out-of-domain Detection for Natural Language Understanding in Dialog Systems Yinhe Zheng Guanyi Chen Minlie Huang 18 121 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 11 24 0 30 Aug 2019
Confidence Regularized Self-Training Yang Zou Zhiding Yu Xiaofeng Liu B. Kumar Jinsong Wang 233 789 0 26 Aug 2019
Density estimation in representation space to predict model uncertainty Tiago Ramalho M. Corbalan UQCV BDL 11 37 0 20 Aug 2019
Regularizing CNN Transfer Learning with Randomised Regression Yang Zhong A. Maki 16 13 0 16 Aug 2019
Entropic Out-of-Distribution Detection David Macêdo T. I. Ren Cleber Zanchettin Adriano Oliveira Teresa B Ludermir OODD UQCV 12 31 0 15 Aug 2019
Dynamic Scale Inference by Entropy Minimization Dequan Wang Evan Shelhamer Bruno A. Olshausen Trevor Darrell 24 7 0 08 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 35 142 0 17 Jul 2019
Natural Adversarial Examples Dan Hendrycks Kevin Zhao Steven Basart Jacob Steinhardt D. Song OODD 53 1,419 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 14 7 0 12 Jun 2019
Analyzing the Role of Model Uncertainty for Electronic Health Records Michael W. Dusenberry Dustin Tran E. Choi Jonas Kemp Jeremy Nixon Ghassen Jerfel Katherine A. Heller Andrew M. Dai 10 117 0 10 Jun 2019
Learning Adaptive Classifiers Synthesis for Generalized Few-Shot Learning Han-Jia Ye Hexiang Hu De-Chuan Zhan 19 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 18 716 0 07 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 24 1,654 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