On Calibration of Modern Neural Networks

14 June 2017

Papers citing "On Calibration of Modern Neural Networks"

34 / 1,084 papers shown

Title
Scalable agent alignment via reward modeling: a research direction Jan Leike David M. Krueger Tom Everitt Miljan Martic Vishal Maini Shane Legg 34 395 0 19 Nov 2018
Learning to Compensate Photovoltaic Power Fluctuations from Images of the Sky by Imitating an Optimal Policy R. Spiess Felix Berkenkamp J. Poland Andreas Krause 18 0 0 13 Nov 2018
Good Initializations of Variational Bayes for Deep Models Simone Rossi Pietro Michiardi Maurizio Filippone BDL 17 21 0 18 Oct 2018
Taming the Cross Entropy Loss Manuel Martínez Rainer Stiefelhagen NoLa 20 46 0 11 Oct 2018
Rate Distortion For Model Compression: From Theory To Practice Weihao Gao Yu-Han Liu Chong-Jun Wang Sewoong Oh 25 31 0 09 Oct 2018
Design by adaptive sampling David H. Brookes Jennifer Listgarten TPM 39 65 0 08 Oct 2018
Unrestricted Adversarial Examples Tom B. Brown Nicholas Carlini Chiyuan Zhang Catherine Olsson Paul Christiano Ian Goodfellow AAML 29 101 0 22 Sep 2018
Evaluating Merging Strategies for Sampling-based Uncertainty Techniques in Object Detection Dimity Miller Feras Dayoub Michael Milford Niko Sünderhauf 23 105 0 17 Sep 2018
Maximum-Entropy Fine-Grained Classification Abhimanyu Dubey O. Gupta Ramesh Raskar Nikhil Naik 17 156 0 16 Sep 2018
Direct Uncertainty Prediction for Medical Second Opinions M. Raghu Katy Blumer Rory Sayres Ziad Obermeyer Robert D. Kleinberg S. Mullainathan Jon M. Kleinberg OOD UD 21 135 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 17 33 0 03 Jul 2018
Accurate Uncertainties for Deep Learning Using Calibrated Regression Volodymyr Kuleshov Nathan Fenner Stefano Ermon BDL UQCV 13 621 0 01 Jul 2018
xGEMs: Generating Examplars to Explain Black-Box Models Shalmali Joshi Oluwasanmi Koyejo Been Kim Joydeep Ghosh MLAU 25 40 0 22 Jun 2018
Countdown Regression: Sharp and Calibrated Survival Predictions Anand Avati Tony Duan Sharon Zhou Kenneth Jung N. Shah A. Ng 6 54 0 21 Jun 2018
To Trust Or Not To Trust A Classifier Heinrich Jiang Been Kim Melody Y. Guan Maya R. Gupta UQCV 30 464 0 30 May 2018
Lightweight Probabilistic Deep Networks Jochen Gast Stefan Roth UQCV OOD BDL 33 180 0 29 May 2018
Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification Dimitrios Milios Raffaello Camoriano Pietro Michiardi Lorenzo Rosasco Maurizio Filippone UQCV 25 74 0 28 May 2018
Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers Yonatan Geifman Guy Uziel Ran El-Yaniv UQCV 17 132 0 21 May 2018
Confidence Scoring Using Whitebox Meta-models with Linear Classifier Probes Tongfei Chen Jirí Navrátil Vijay Iyengar Karthikeyan Shanmugam 10 42 0 14 May 2018
Strong Baselines for Neural Semi-supervised Learning under Domain Shift Sebastian Ruder Barbara Plank 9 171 0 25 Apr 2018
360° Stance Detection Sebastian Ruder John Glover Afshin Mehrabani Parsa Ghaffari 9 9 0 03 Apr 2018
Calibrated Prediction Intervals for Neural Network Regressors Gil Keren N. Cummins Björn Schuller UQCV 24 31 0 26 Mar 2018
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning Nicolas Papernot Patrick McDaniel OOD AAML 8 502 0 13 Mar 2018
Analyzing Uncertainty in Neural Machine Translation Myle Ott Michael Auli David Grangier MarcÁurelio Ranzato UQLM 31 270 0 28 Feb 2018
Training wide residual networks for deployment using a single bit for each weight Mark D Mcdonnell MQ 27 71 0 23 Feb 2018
DeepMatch: Balancing Deep Covariate Representations for Causal Inference Using Adversarial Training Nathan Kallus CML OOD 19 74 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 25 546 0 14 Feb 2018
Learning Confidence for Out-of-Distribution Detection in Neural Networks Terrance Devries Graham W. Taylor OOD OODD 17 581 0 13 Feb 2018
Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples Kimin Lee Honglak Lee Kibok Lee Jinwoo Shin OODD 64 872 0 26 Nov 2017
Implicit Weight Uncertainty in Neural Networks Nick Pawlowski Andrew Brock Matthew C. H. Lee Martin Rajchl Ben Glocker BDL UQCV 30 95 0 03 Nov 2017
Discriminative k-shot learning using probabilistic models Matthias Bauer Mateo Rojas-Carulla J. Swiatkowski Bernhard Schölkopf Richard Turner VLM 18 71 0 01 Jun 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,661 0 05 Dec 2016
Estimating Uncertainty Online Against an Adversary Volodymyr Kuleshov Stefano Ermon OOD 19 7 0 13 Jul 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015