On Calibration of Modern Neural Networks

14 June 2017

Papers citing "On Calibration of Modern Neural Networks"

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Title
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 41 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 26 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
Test Selection for Deep Learning Systems Wei Ma Mike Papadakis Anestis Tsakmalis Maxime Cordy Yves Le Traon OOD 21 92 0 30 Apr 2019
Acoustic scene classification using teacher-student learning with soft-labels Hee-Soo Heo Jee-weon Jung Hye-jin Shim Ha-Jin Yu 24 22 0 23 Apr 2019
Convolutional Neural Networks for Classification of Alzheimer's Disease: Overview and Reproducible Evaluation Junhao Wen Elina Thibeau-Sutre Mauricio Diaz-Melo J. Samper-González A. Routier Simona Bottani Didier Dormont S. Durrleman Ninon Burgos O. Colliot 27 506 0 16 Apr 2019
Measuring Calibration in Deep Learning Jeremy Nixon Michael W. Dusenberry Ghassen Jerfel Timothy Nguyen Jeremiah Zhe Liu Linchuan Zhang Dustin Tran UQCV 8 476 0 02 Apr 2019
Overcoming Catastrophic Forgetting with Unlabeled Data in the Wild Kibok Lee Kimin Lee Jinwoo Shin Honglak Lee CLL 43 201 0 29 Mar 2019
The Algorithmic Automation Problem: Prediction, Triage, and Human Effort M. Raghu Katy Blumer G. Corrado Jon M. Kleinberg Ziad Obermeyer S. Mullainathan 21 138 0 28 Mar 2019
Combination of Multiple Global Descriptors for Image Retrieval HeeJae Jun ByungSoo Ko Youngjoon Kim Insik Kim Jongtack Kim 31 59 0 26 Mar 2019
Interpreting Neural Networks Using Flip Points Roozbeh Yousefzadeh D. O’Leary AAML FAtt 22 17 0 21 Mar 2019
Calibration of Encoder Decoder Models for Neural Machine Translation Aviral Kumar Sunita Sarawagi 27 98 0 03 Mar 2019
Deep learning in bioinformatics: introduction, application, and perspective in big data era Yu Li Chao Huang Lizhong Ding Zhongxiao Li Yijie Pan Xin Gao AI4CE 24 295 0 28 Feb 2019
Collaborative Sampling in Generative Adversarial Networks Yuejiang Liu Parth Kothari Alexandre Alahi TTA 28 16 0 02 Feb 2019
Using Pre-Training Can Improve Model Robustness and Uncertainty Dan Hendrycks Kimin Lee Mantas Mazeika NoLa 34 720 0 28 Jan 2019
Testing Conditional Independence in Supervised Learning Algorithms David S. Watson Marvin N. Wright CML 29 52 0 28 Jan 2019
Money on the Table: Statistical information ignored by Softmax can improve classifier accuracy Charles B. Delahunt C. Mehanian J. Nathan Kutz 16 1 0 26 Jan 2019
Improving Adversarial Robustness via Promoting Ensemble Diversity Tianyu Pang Kun Xu Chao Du Ning Chen Jun Zhu AAML 41 434 0 25 Jan 2019
Maximum Likelihood with Bias-Corrected Calibration is Hard-To-Beat at Label Shift Adaptation Amr M. Alexandari A. Kundaje Avanti Shrikumar 11 9 0 21 Jan 2019
Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled Data Yinhao Zhu N. Zabaras P. Koutsourelakis P. Perdikaris PINN AI4CE 46 854 0 18 Jan 2019
A witness function based construction of discriminative models using Hermite polynomials H. Mhaskar A. Cloninger Xiuyuan Cheng 24 9 0 10 Jan 2019
Can You Trust This Prediction? Auditing Pointwise Reliability After Learning Peter F. Schulam Suchi Saria OOD 27 103 0 02 Jan 2019
Opportunistic Learning: Budgeted Cost-Sensitive Learning from Data Streams Mohammad Kachuee Orpaz Goldstein Kimmo Karkkainen Sajad Darabi Majid Sarrafzadeh OOD 31 31 0 02 Jan 2019
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem Matthias Hein Maksym Andriushchenko Julian Bitterwolf OODD 55 553 0 13 Dec 2018
Deep Anomaly Detection with Outlier Exposure Dan Hendrycks Mantas Mazeika Thomas G. Dietterich OODD 31 1,453 0 11 Dec 2018
Knowing what you know in brain segmentation using Bayesian deep neural networks Patrick McClure Nao Rho J. Lee Jakub R. Kaczmarzyk C. Zheng Satrajit S. Ghosh D. Nielson Adam G. Thomas P. Bandettini Francisco Pereira UQCV 3DV BDL 24 52 0 03 Dec 2018
XNet: A convolutional neural network (CNN) implementation for medical X-Ray image segmentation suitable for small datasets Joseph Aylett-Bullock C. Cuesta-Lázaro Arnau Quera-Bofarull 27 101 0 03 Dec 2018
Online Abstraction with MDP Homomorphisms for Deep Learning Ondrej Biza Robert W. Platt OffRL 26 21 0 30 Nov 2018
Evaluating Bayesian Deep Learning Methods for Semantic Segmentation Jishnu Mukhoti Y. Gal UQCV BDL 33 219 0 30 Nov 2018
Calibrating Uncertainties in Object Localization Task Buu Phan Rick Salay Krzysztof Czarnecki Vahdat Abdelzad Taylor Denouden Sachin Vernekar UQCV 24 22 0 27 Nov 2018
Label-Noise Robust Generative Adversarial Networks Takuhiro Kaneko Yoshitaka Ushiku Tatsuya Harada NoLa 27 60 0 27 Nov 2018