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Dual Representation Learning for Out-of-Distribution Detection

19 June 2022

Papers citing "Dual Representation Learning for Out-of-Distribution Detection"

45 / 45 papers shown

Title
Double Descent Meets Out-of-Distribution Detection: Theoretical Insights and Empirical Analysis on the role of model complexity Mouin Ben Ammar David Brellmann Arturo Mendoza Antoine Manzanera Gianni Franchi OODD 104 0 0 04 Nov 2024
Linking Neural Collapse and L2 Normalization with Improved Out-of-Distribution Detection in Deep Neural Networks J. Haas William Yolland B. Rabus OODD 75 20 0 17 Sep 2022
Positive Difference Distribution for Image Outlier Detection using Normalizing Flows and Contrastive Data R. Schmier Ullrich Kothe C. Straehle 52 5 0 30 Aug 2022
Out-of-Distribution Detection with Deep Nearest Neighbors Yiyou Sun Yifei Ming Xiaojin Zhu Yixuan Li OODD 206 533 0 13 Apr 2022
VFDS: Variational Foresight Dynamic Selection in Bayesian Neural Networks for Efficient Human Activity Recognition Randy Ardywibowo Shahin Boluki Zhangyang Wang Bobak J. Mortazavi Shuai Huang Xiaoning Qian 30 2 0 31 Mar 2022
How to Exploit Hyperspherical Embeddings for Out-of-Distribution Detection? Yifei Ming Yiyou Sun Ousmane Amadou Dia Yixuan Li OODD 117 103 0 08 Mar 2022
Provable Guarantees for Understanding Out-of-distribution Detection Peyman Morteza Yixuan Li OODD 105 95 0 01 Dec 2021
ReAct: Out-of-distribution Detection With Rectified Activations Yiyou Sun Chuan Guo Yixuan Li OODD 115 485 0 24 Nov 2021
Evolving Decomposed Plasticity Rules for Information-Bottlenecked Meta-Learning Fan Wang Hao Tian Haoyi Xiong Hua Wu Jie Fu Yang Cao Yu Kang Haifeng Wang AI4CE 72 3 0 08 Sep 2021
Revealing the Distributional Vulnerability of Discriminators by Implicit Generators Zhilin Zhao LongBing Cao Kun-Yu Lin 72 11 0 23 Aug 2021
MOS: Towards Scaling Out-of-distribution Detection for Large Semantic Space Rui Huang Yixuan Li OODD 85 249 0 05 May 2021
Energy-based Out-of-distribution Detection Weitang Liu Xiaoyun Wang John Douglas Owens Yixuan Li OODD 273 1,374 0 08 Oct 2020
CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances Jihoon Tack Sangwoo Mo Jongheon Jeong Jinwoo Shin OODD 85 604 0 16 Jul 2020
Contrastive Training for Improved Out-of-Distribution Detection Jim Winkens Rudy Bunel Abhijit Guha Roy Robert Stanforth Vivek Natarajan ... Alan Karthikesalingam Simon A. A. Kohl taylan. cemgil S. M. Ali Eslami Olaf Ronneberger OODD 132 242 0 10 Jul 2020
Hybrid Models for Open Set Recognition Hongjie Zhang Ang Li Jie Guo Yanwen Guo BDL 146 185 0 27 Mar 2020
Generalized ODIN: Detecting Out-of-distribution Image without Learning from Out-of-distribution Data Yen-Chang Hsu Yilin Shen Hongxia Jin Z. Kira OODD 109 577 0 26 Feb 2020
Learning Robust Representations via Multi-View Information Bottleneck Marco Federici Anjan Dutta Patrick Forré Nate Kushman Zeynep Akata SLR 63 258 0 17 Feb 2020
Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty Dan Hendrycks Mantas Mazeika Saurav Kadavath Basel Alomair OOD SSL 56 950 0 28 Jun 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 209 728 0 07 Jun 2019
Using Pre-Training Can Improve Model Robustness and Uncertainty Dan Hendrycks Kimin Lee Mantas Mazeika NoLa 81 727 0 28 Jan 2019
Out-of-Distribution Detection using Multiple Semantic Label Representations Gabi Shalev Yossi Adi Joseph Keshet OODD 79 85 0 20 Aug 2018
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks Kimin Lee Kibok Lee Honglak Lee Jinwoo Shin OODD 192 2,063 0 10 Jul 2018
Predictive Uncertainty Estimation via Prior Networks A. Malinin Mark Gales UD BDL EDL UQCV PER 197 923 0 28 Feb 2018
MINE: Mutual Information Neural Estimation Mohamed Ishmael Belghazi A. Baratin Sai Rajeswar Sherjil Ozair Yoshua Bengio Aaron Courville R. Devon Hjelm DRL 200 1,285 0 12 Jan 2018
Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples Kimin Lee Honglak Lee Kibok Lee Jinwoo Shin OODD 128 882 0 26 Nov 2017
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 299 5,871 0 14 Jun 2017
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 800 132,454 0 12 Jun 2017
Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks Shiyu Liang Yixuan Li R. Srikant UQCV OODD 171 2,082 0 08 Jun 2017
Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning Takeru Miyato S. Maeda Masanori Koyama S. Ishii GAN 153 2,739 0 13 Apr 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 842 5,847 0 05 Dec 2016
Deep Variational Information Bottleneck Alexander A. Alemi Ian S. Fischer Joshua V. Dillon Kevin Patrick Murphy 130 1,728 0 01 Dec 2016
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization Ramprasaath R. Selvaraju Michael Cogswell Abhishek Das Ramakrishna Vedantam Devi Parikh Dhruv Batra FAtt 335 20,110 0 07 Oct 2016
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks Dan Hendrycks Kevin Gimpel UQCV 176 3,480 0 07 Oct 2016
Densely Connected Convolutional Networks Gao Huang Zhuang Liu Laurens van der Maaten Kilian Q. Weinberger PINN 3DV 803 36,892 0 25 Aug 2016
Multi-way Monte Carlo Method for Linear Systems Tao Wu D. Gleich 23 9 0 15 Aug 2016
Monte Carlo Markov Chain Algorithms for Sampling Strongly Rayleigh Distributions and Determinantal Point Processes Nima Anari S. Gharan A. Rezaei 54 130 0 16 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,510 0 10 Dec 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 863 9,353 0 06 Jun 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 282 19,129 0 20 Dec 2014
Going Deeper with Convolutions Christian Szegedy Wei Liu Yangqing Jia P. Sermanet Scott E. Reed Dragomir Anguelov D. Erhan Vincent Vanhoucke Andrew Rabinovich 494 43,698 0 17 Sep 2014
Microsoft COCO: Common Objects in Context Nayeon Lee Michael Maire Serge J. Belongie Lubomir Bourdev Ross B. Girshick James Hays Pietro Perona Deva Ramanan C. L. Zitnick Piotr Dollár ObjD 434 43,832 0 01 May 2014
Describing Textures in the Wild Mircea Cimpoi Subhransu Maji Iasonas Kokkinos S. Mohamed Andrea Vedaldi 3DV 146 2,693 0 14 Nov 2013
Determinantal point processes for machine learning Alex Kulesza B. Taskar 272 1,140 0 25 Jul 2012
Representation Learning: A Review and New Perspectives Yoshua Bengio Aaron Courville Pascal Vincent OOD SSL 284 12,460 0 24 Jun 2012
Learning Determinantal Point Processes Alex Kulesza B. Taskar 86 162 0 14 Feb 2012