v1v2 (latest)

On Calibration of Modern Neural Networks

International Conference on Machine Learning (ICML), 2017

14 June 2017

Papers citing "On Calibration of Modern Neural Networks"

50 / 3,756 papers shown

Title
Task adapted reconstruction for inverse problems J. Adler Sebastian Lunz Olivier Verdier Carola-Bibiane Schönlieb Ozan Oktem 141 48 0 27 Aug 2018
ParaNet - Using Dense Blocks for Early Inference Jo Chuang Eric Tsai Kevin Huang Jay Fetter PINN 40 1 0 24 Aug 2018
Discriminative out-of-distribution detection for semantic segmentation Petra Bevandić Ivan Kreso Marin Orsic Sinisa Segvic 168 86 0 23 Aug 2018
Improving Simple Models with Confidence ProfilesNeural Information Processing Systems (NeurIPS), 2018 Amit Dhurandhar Karthikeyan Shanmugam Ronny Luss Peder Olsen 160 47 0 19 Jul 2018
Zap: Making Predictions Based on Online User Behavior Yuri Chervonyi Dragos Harabor Brian Zhang Josh Sacks VLM 72 0 0 16 Jul 2018
Direct Uncertainty Prediction for Medical Second OpinionsInternational Conference on Machine Learning (ICML), 2018 M. Raghu Katy Blumer Rory Sayres Ziad Obermeyer Robert D. Kleinberg S. Mullainathan Jon M. Kleinberg OOD UD 385 144 0 04 Jul 2018
Behaviour Policy Estimation in Off-Policy Policy Evaluation: Calibration Matters Aniruddh Raghu Omer Gottesman Yao Liu Matthieu Komorowski A. Faisal Finale Doshi-Velez Emma Brunskill OffRL 153 35 0 03 Jul 2018
Uncertainty in the Variational Information Bottleneck Alexander A. Alemi Ian S. Fischer Joshua V. Dillon 240 106 0 02 Jul 2018
Accurate Uncertainties for Deep Learning Using Calibrated RegressionInternational Conference on Machine Learning (ICML), 2018 Volodymyr Kuleshov Nathan Fenner Stefano Ermon BDL UQCV 516 736 0 01 Jul 2018
A New Angle on L2 Regularization T. Tanay Lewis D. Griffin LLMSV 112 5 0 28 Jun 2018
Adversarial Distillation of Bayesian Neural Network PosteriorsInternational Conference on Machine Learning (ICML), 2018 Kuan-Chieh Wang Paul Vicol James Lucas Li Gu Roger C. Grosse R. Zemel UQCV GAN AAML BDL 144 58 0 27 Jun 2018
xGEMs: Generating Examplars to Explain Black-Box Models Shalmali Joshi Oluwasanmi Koyejo Been Kim Joydeep Ghosh MLAU 140 41 0 22 Jun 2018
Countdown Regression: Sharp and Calibrated Survival Predictions Anand Avati Tony Duan Sharon Zhou Kenneth Jung N. Shah A. Ng 448 60 0 21 Jun 2018
Built-in Vulnerabilities to Imperceptible Adversarial Perturbations T. Tanay Jerone T. A. Andrews Lewis D. Griffin 148 7 0 19 Jun 2018
Impostor Networks for Fast Fine-Grained Recognition V. Lebedev Artem Babenko Victor Lempitsky 113 3 0 13 Jun 2018
Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models Kurtland Chua Roberto Calandra R. McAllister Sergey Levine BDL 407 1,388 0 30 May 2018
To Trust Or Not To Trust A Classifier Heinrich Jiang Been Kim Melody Y. Guan Maya R. Gupta UQCV 433 492 0 30 May 2018
Lightweight Probabilistic Deep Networks Jochen Gast Stefan Roth UQCV OOD BDL 208 194 0 29 May 2018
Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification Dimitrios Milios Raffaello Camoriano Pietro Michiardi Lorenzo Rosasco Maurizio Filippone UQCV 177 82 0 28 May 2018
Calibrating Deep Convolutional Gaussian Processes Gia-Lac Tran Edwin V. Bonilla John P. Cunningham Pietro Michiardi Maurizio Filippone BDL UQCV 126 43 0 26 May 2018
Uncertainty-Aware Attention for Reliable Interpretation and Prediction Jay Heo Haebeom Lee Saehoon Kim Juho Lee Kwang Joon Kim Eunho Yang Sung Ju Hwang OOD 143 90 0 24 May 2018
Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers Yonatan Geifman Guy Uziel Ran El-Yaniv UQCV 301 149 0 21 May 2018
Confidence Scoring Using Whitebox Meta-models with Linear Classifier Probes Tongfei Chen Jirí Navrátil Vijay Iyengar Karthikeyan Shanmugam 137 48 0 14 May 2018
Progressive Neural Networks for Image Classification Zhi Zhang G. Ning Yigang Cen Yongqian Li Zhiqun Zhao Hao Sun Zhihai He 48 8 0 25 Apr 2018
Strong Baselines for Neural Semi-supervised Learning under Domain Shift Sebastian Ruder Barbara Plank 131 177 0 25 Apr 2018
Pathologies of Neural Models Make Interpretations DifficultConference on Empirical Methods in Natural Language Processing (EMNLP), 2018 Shi Feng Eric Wallace Alvin Grissom II Mohit Iyyer Pedro Rodriguez Jordan L. Boyd-Graber AAML FAtt 268 330 0 20 Apr 2018
The Limits and Potentials of Deep Learning for Robotics Niko Sünderhauf Oliver Brock Walter J. Scheirer R. Hadsell Dieter Fox ... B. Upcroft Pieter Abbeel Wolfram Burgard Michael Milford Peter Corke 205 545 0 18 Apr 2018
KS(conf ): A Light-Weight Test if a ConvNet Operates Outside of Its Specifications Rémy Sun Christoph H. Lampert 118 7 0 11 Apr 2018
Improving Confidence Estimates for Unfamiliar Examples Zhizhong Li Derek Hoiem 217 11 0 09 Apr 2018
360° Stance Detection Sebastian Ruder John Glover Afshin Mehrabani Parsa Ghaffari 66 9 0 03 Apr 2018
Calibrated Prediction Intervals for Neural Network Regressors Gil Keren N. Cummins Björn Schuller UQCV 272 31 0 26 Mar 2018
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning Nicolas Papernot Patrick McDaniel OOD AAML 320 545 0 13 Mar 2018
Stochastic Activation Pruning for Robust Adversarial Defense Guneet Singh Dhillon Kamyar Azizzadenesheli Zachary Chase Lipton Jeremy Bernstein Jean Kossaifi Aran Khanna Anima Anandkumar AAML 296 569 0 05 Mar 2018
Analyzing Uncertainty in Neural Machine TranslationInternational Conference on Machine Learning (ICML), 2018 Myle Ott Michael Auli David Grangier MarcÁurelio Ranzato UQLM 453 283 0 28 Feb 2018
Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNsNeural Information Processing Systems (NeurIPS), 2018 T. Garipov Pavel Izmailov Dmitrii Podoprikhin Dmitry Vetrov A. Wilson UQCV 512 841 0 27 Feb 2018
Training wide residual networks for deployment using a single bit for each weight Mark D Mcdonnell MQ 200 73 0 23 Feb 2018
Diversity regularization in deep ensembles Changjian Shui A. Mozafari Jonathan Marek Ihsen Hedhli Christian Gagné UQCV 108 15 0 22 Feb 2018
A General Framework for Abstention Under Label Shift Amr M. Alexandari A. Kundaje Avanti Shrikumar 194 2 0 20 Feb 2018
Distribution Matching in Variational Inference Mihaela Rosca Balaji Lakshminarayanan S. Mohamed GAN CML DRL 343 101 0 19 Feb 2018
A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks Jeffrey Chan Valerio Perrone J. Spence Paul A. Jenkins Sara Mathieson Yun S. Song 442 119 0 16 Feb 2018
Improved GQ-CNN: Deep Learning Model for Planning Robust Grasps Maciej Jaskowski J. Swiatkowski Michal Zajac Maciek Klimek Jarek Potiuk Piotr Rybicki P. Polatowski Przemyslaw Walczyk Kacper Nowicki Marek Cygan 88 9 0 16 Feb 2018
DeepMatch: Balancing Deep Covariate Representations for Causal Inference Using Adversarial Training Nathan Kallus CML OOD 186 83 0 15 Feb 2018
Using Trusted Data to Train Deep Networks on Labels Corrupted by Severe Noise Dan Hendrycks Mantas Mazeika Duncan Wilson Kevin Gimpel NoLa 598 589 0 14 Feb 2018
Learning Confidence for Out-of-Distribution Detection in Neural Networks Terrance Devries Graham W. Taylor OOD OODD 262 628 0 13 Feb 2018
Predicting Adversarial Examples with High Confidence A. Galloway Graham W. Taylor M. Moussa AAML 127 9 0 13 Feb 2018
Temporal Stability in Predictive Process Monitoring Irene Teinemaa Marlon Dumas A. Leontjeva F. Maggi 142 58 0 12 Dec 2017
Noisy Natural Gradient as Variational Inference Guodong Zhang Shengyang Sun David Duvenaud Roger C. Grosse ODL 250 220 0 06 Dec 2017
Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples Kimin Lee Honglak Lee Kibok Lee Jinwoo Shin OODD 432 922 0 26 Nov 2017
Adversarial Phenomenon in the Eyes of Bayesian Deep Learning Ambrish Rawat Martin Wistuba Maria-Irina Nicolae BDL AAML 109 41 0 22 Nov 2017
Predict Responsibly: Improving Fairness and Accuracy by Learning to Defer David Madras T. Pitassi R. Zemel FaML 341 254 0 17 Nov 2017