To Trust Or Not To Trust A Classifier

30 May 2018

Papers citing "To Trust Or Not To Trust A Classifier"

21 / 21 papers shown

Title
Unveiling AI's Blind Spots: An Oracle for In-Domain, Out-of-Domain, and Adversarial Errors Shuangpeng Han Mengmi Zhang 293 0 0 03 Oct 2024
Anomalous Example Detection in Deep Learning: A Survey Saikiran Bulusu B. Kailkhura Yue Liu P. Varshney D. Song AAML 103 47 0 16 Mar 2020
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning Nicolas Papernot Patrick McDaniel OOD AAML 108 505 0 13 Mar 2018
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 216 5,774 0 14 Jun 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 296 4,667 0 15 Mar 2017
Density Level Set Estimation on Manifolds with DBSCAN Heinrich Jiang 42 32 0 10 Mar 2017
Online Learning with Abstention Corinna Cortes Giulia DeSalvo Claudio Gentile M. Mohri Scott Yang 97 47 0 09 Mar 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 535 5,748 0 05 Dec 2016
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks Dan Hendrycks Kevin Gimpel UQCV 111 3,420 0 07 Oct 2016
On the Safety of Machine Learning: Cyber-Physical Systems, Decision Sciences, and Data Products Kush R. Varshney H. Alemzadeh 59 223 0 05 Oct 2016
Concrete Problems in AI Safety Dario Amodei C. Olah Jacob Steinhardt Paul Christiano John Schulman Dandelion Mané 153 2,371 0 21 Jun 2016
Rethinking the Inception Architecture for Computer Vision Christian Szegedy Vincent Vanhoucke Sergey Ioffe Jonathon Shlens Z. Wojna 3DV BDL 539 27,231 0 02 Dec 2015
Efficient Learning by Directed Acyclic Graph For Resource Constrained Prediction Joseph Wang K. Trapeznikov Venkatesh Saligrama 45 49 0 26 Oct 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 526 9,233 0 06 Jun 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 189 18,922 0 20 Dec 2014
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images Anh Totti Nguyen J. Yosinski Jeff Clune AAML 136 3,261 0 05 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.0K 99,991 0 04 Sep 2014
Cluster Trees on Manifolds Sivaraman Balakrishnan S. Narayanan Alessandro Rinaldo Aarti Singh Larry A. Wasserman 47 45 0 24 Jul 2013
Minimax Manifold Estimation Christopher R. Genovese M. Perone-Pacifico I. Verdinelli Larry A. Wasserman 72 128 0 04 Jul 2010
Adaptive Hausdorff estimation of density level sets Aarti Singh Clayton Scott Robert D. Nowak 83 84 0 25 Aug 2009
Generalized density clustering Alessandro Rinaldo Larry A. Wasserman 80 163 0 20 Jul 2009