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Training Confidence-calibrated Classifiers for Detecting
  Out-of-Distribution Samples

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
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
Unsupervised Out-of-Distribution Detection by Maximum Classifier Discrepancy
Qing Yu
Kiyoharu Aizawa
OODD
11
163
0
14 Aug 2019
Natural Adversarial Examples
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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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