On Calibration of Modern Neural Networks

14 June 2017

Papers citing "On Calibration of Modern Neural Networks"

25 / 1,275 papers shown

Title
Countdown Regression: Sharp and Calibrated Survival Predictions Anand Avati Tony Duan Sharon Zhou Kenneth Jung N. Shah A. Ng 22 55 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 35 74 0 28 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 20 87 0 24 May 2018
Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers Yonatan Geifman Guy Uziel Ran El-Yaniv UQCV 17 134 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 22 171 0 25 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 17 522 0 18 Apr 2018
360° Stance Detection Sebastian Ruder John Glover Afshin Mehrabani Parsa Ghaffari 14 9 0 03 Apr 2018
Calibrated Prediction Intervals for Neural Network Regressors Gil Keren N. Cummins Björn Schuller UQCV 30 31 0 26 Mar 2018
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning Nicolas Papernot Patrick McDaniel OOD AAML 13 504 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 33 545 0 05 Mar 2018
Analyzing Uncertainty in Neural Machine Translation Myle Ott Michael Auli David Grangier MarcÁurelio Ranzato UQLM 43 271 0 28 Feb 2018
Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs T. Garipov Pavel Izmailov Dmitrii Podoprikhin Dmitry Vetrov A. Wilson UQCV 27 734 0 27 Feb 2018
Training wide residual networks for deployment using a single bit for each weight Mark D Mcdonnell MQ 35 71 0 23 Feb 2018
DeepMatch: Balancing Deep Covariate Representations for Causal Inference Using Adversarial Training Nathan Kallus CML OOD 27 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 70 547 0 14 Feb 2018
Learning Confidence for Out-of-Distribution Detection in Neural Networks Terrance Devries Graham W. Taylor OOD OODD 43 582 0 13 Feb 2018
Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples Kimin Lee Honglak Lee Kibok Lee Jinwoo Shin OODD 70 873 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 20 71 0 01 Jun 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,695 0 05 Dec 2016
Estimating Uncertainty Online Against an Adversary Volodymyr Kuleshov Stefano Ermon OOD 27 7 0 13 Jul 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,167 0 06 Jun 2015