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1711.09325
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Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples
26 November 2017
Kimin Lee
Honglak Lee
Kibok Lee
Jinwoo Shin
OODD
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Papers citing
"Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples"
24 / 174 papers shown
Title
Density estimation in representation space to predict model uncertainty
Tiago Ramalho
M. Corbalan
UQCV
BDL
11
37
0
20 Aug 2019
Unsupervised Out-of-Distribution Detection by Maximum Classifier Discrepancy
Qing Yu
Kiyoharu Aizawa
OODD
11
163
0
14 Aug 2019
Natural Adversarial Examples
Dan Hendrycks
Kevin Zhao
Steven Basart
Jacob Steinhardt
D. Song
OODD
50
1,419
0
16 Jul 2019
Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data
Simao Eduardo
A. Nazábal
Christopher K. I. Williams
Charles Sutton
DRL
11
32
0
15 Jul 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
18
716
0
07 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
Analysis of Confident-Classifiers for Out-of-distribution Detection
Sachin Vernekar
Ashish Gaurav
Taylor Denouden
Buu Phan
Vahdat Abdelzad
Rick Salay
Krzysztof Czarnecki
OODD
18
18
0
27 Apr 2019
Out-of-Distribution Detection for Generalized Zero-Shot Action Recognition
Devraj Mandal
Sanath Narayan
Sai Kumar Dwivedi
Vikram Gupta
Shuaib Ahmed
F. Khan
Ling Shao
OODD
14
141
0
18 Apr 2019
Overcoming Catastrophic Forgetting with Unlabeled Data in the Wild
Kibok Lee
Kimin Lee
Jinwoo Shin
Honglak Lee
CLL
29
201
0
29 Mar 2019
Deep CNN-based Multi-task Learning for Open-Set Recognition
Poojan Oza
Vishal M. Patel
16
35
0
07 Mar 2019
Enhancing the Robustness of Deep Neural Networks by Boundary Conditional GAN
Ke Sun
Zhanxing Zhu
Zhouchen Lin
AAML
17
20
0
28 Feb 2019
The Importance of Metric Learning for Robotic Vision: Open Set Recognition and Active Learning
Benjamin J. Meyer
Tom Drummond
14
33
0
27 Feb 2019
Using Pre-Training Can Improve Model Robustness and Uncertainty
Dan Hendrycks
Kimin Lee
Mantas Mazeika
NoLa
17
717
0
28 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
40
552
0
13 Dec 2018
Deep Anomaly Detection with Outlier Exposure
Dan Hendrycks
Mantas Mazeika
Thomas G. Dietterich
OODD
31
1,449
0
11 Dec 2018
Building robust classifiers through generation of confident out of distribution examples
K. Sricharan
Ashok Srivastava
OOD
8
31
0
01 Dec 2018
Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift
Stephan Rabanser
Stephan Günnemann
Zachary Chase Lipton
27
357
0
29 Oct 2018
Out-of-Distribution Detection Using an Ensemble of Self Supervised Leave-out Classifiers
Apoorv Vyas
Nataraj Jammalamadaka
Xia Zhu
Dipankar Das
Bharat Kaul
Theodore L. Willke
OODD
14
246
0
04 Sep 2018
Controlling Over-generalization and its Effect on Adversarial Examples Generation and Detection
Mahdieh Abbasi
Arezoo Rajabi
A. Mozafari
R. Bobba
Christian Gagné
AAML
16
9
0
21 Aug 2018
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks
Kimin Lee
Kibok Lee
Honglak Lee
Jinwoo Shin
OODD
21
1,994
0
10 Jul 2018
Hierarchical Novelty Detection for Visual Object Recognition
Kibok Lee
Kimin Lee
Kyle Min
Y. Zhang
Jinwoo Shin
Honglak Lee
BDL
44
67
0
02 Apr 2018
Learning Confidence for Out-of-Distribution Detection in Neural Networks
Terrance Devries
Graham W. Taylor
OOD
OODD
15
581
0
13 Feb 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
276
5,661
0
05 Dec 2016
Improving neural networks by preventing co-adaptation of feature detectors
Geoffrey E. Hinton
Nitish Srivastava
A. Krizhevsky
Ilya Sutskever
Ruslan Salakhutdinov
VLM
266
7,636
0
03 Jul 2012
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