Energy-based Out-of-distribution Detection

Weitang Liu, Xiaoyun Wang, John D. Owens, Yixuan Li

Type: Preprint

Publication Date: 2020-01-01

Citations: 383

DOI: https://doi.org/10.48550/arxiv.2010.03759

View Publication

Locations

arXiv (Cornell University) - View
DataCite API - View

Similar Works

Action	Title	Year	Authors
+ PDF Chat	Entropic Out-of-Distribution Detection: Seamless Detection of Unknown Examples	2021	David Macêdo Tsang Ing Ren Cleber Zanchettin Adriano L. I. Oliveira Teresa B. Ludermir
+	Hybrid Energy Based Model in the Feature Space for Out-of-Distribution Detection	2023	Marc Lafon Elias Ramzi Clément Rambour Nicolas Thome
+ PDF Chat	Energy Correction Model in the Feature Space for Out-of-Distribution Detection	2024	Marc Lafon Clément Rambour Nicolas Thome
+ PDF Chat	Entropic Out-of-Distribution Detection	2021	David Macêdo Tsang Ing Ren Cleber Zanchettin Adriano L. I. Oliveira Teresa B. Ludermir
+	Augmenting Softmax Information for Selective Classification with Out-of-Distribution Data	2022	Guoxuan Xia Christos-Savvas Bouganis
+ PDF Chat	FEVER-OOD: Free Energy Vulnerability Elimination for Robust Out-of-Distribution Detection	2024	Brian K. S. Isaac-Medina Mauricio Che Yona Falinie A. Gaus Samet Akçay Toby P. Breckon
+	A Simple Test-Time Method for Out-of-Distribution Detection	2022	Ke Fan Yikai Wang Qian Yu Da Li Yanwei Fu
+	Isotropy Maximization Loss and Entropic Score: Accurate, Fast, Efficient, Scalable, and Turnkey Neural Networks Out-of-Distribution Detection Based on The Principle of Maximum Entropy	2019	David Macêdo Tsang Ing Ren Cleber Zanchettin Adriano L. I. Oliveira Teresa B. Ludermir
+	ReAct: Out-of-distribution Detection With Rectified Activations	2021	Yiyou Sun Chuan Guo Yixuan Li
+	Predicted Embedding Power Regression for Large-Scale Out-of-Distribution Detection	2023	Hong Yang William Gebhardt Alexander G. Ororbia Travis Desell
+	MOOD: Multi-level Out-of-distribution Detection	2021	Ziqian Lin Sreya Dutta Roy Yixuan Li
+	Out-of-Distribution Detection & Applications With Ablated Learned Temperature Energy	2024	Will LeVine Benjamin Pikus J. R. Phillips Berk Norman Fernando Amat Gil Sean M. Hendryx
+ PDF Chat	Revisiting Energy-Based Model for Out-of-Distribution Detection	2024	Yifan Wu Xichen Ye Songmin Dai Dengye Pan Xiaoqiang Li Weizhong Zhang Yifan Chen
+ PDF Chat	MOOD: Multi-level Out-of-distribution Detection	2021	Ziqian Lin Sreya Dutta Roy Yixuan Li
+ PDF Chat	Semantic Driven Energy based Out-of-Distribution Detection	2022	Abhishek Joshi Sathish Chalasani Kiran Nanjunda Iyer
+	Semantic Driven Energy based Out-of-Distribution Detection	2022	Abhishek Joshi Sathish Chalasani Kiran Nanjunda Iyer
+ PDF Chat	FOOD: Fast Out-Of-Distribution Detector	2021	Guy Amit Moshe Levy Ishai Rosenberg Asaf Shabtai Yuval Elovici
+ PDF Chat	Neural Mean Discrepancy for Efficient Out-of-Distribution Detection	2022	Xin Dong Junfeng Guo Ang Li Wei-Te Ting Cong Liu H.T. Kung
+	FOOD: Fast Out-Of-Distribution Detector	2020	Guy Amit Moshe Levy Ishai Rosenberg Asaf Shabtai Yuval Elovici
+	FOOD: Fast Out-Of-Distribution Detector	2020	Guy Amit Moshe Levy Ishai Rosenberg Asaf Shabtai Yuval Elovici

Works That Cite This (195)

Action	Title	Year	Authors
+ PDF Chat	Provable Guarantees for Understanding Out-of-Distribution Detection	2022	Peyman Morteza Yixuan Li
+ PDF Chat	iDECODe: In-Distribution Equivariance for Conformal Out-of-Distribution Detection	2022	Ramneet Kaur Susmit Jha Anirban Roy Sangdon Park Edgar Dobriban Oleg Sokolsky Insup Lee
+ PDF Chat	Open Set Action Recognition via Multi-Label Evidential Learning	2023	Chen Zhao Dawei Du Anthony Hoogs Christopher Funk
+ PDF Chat	Robust Generalization Against Photon-Limited Corruptions via Worst-Case Sharpness Minimization	2023	Zhuo Huang Miaoxi Zhu Xiaobo Xia Li Shen Jun Yu Chen Gong Bo Han Bo Du Tongliang Liu
+ PDF Chat	SAFE: Sensitivity-Aware Features for Out-of-Distribution Object Detection	2023	Samuel H. Wilson Tobias Fischer Feras Dayoub Dimity Miller Niko Sünderhauf
+ PDF Chat	Multiobjective evolutionary pruning of Deep Neural Networks with Transfer Learning for improving their performance and robustness	2023	Javier Poyatos Daniel Molina Aitor Martínez-Seras Javier Del Ser Francisco Herrera
+ PDF Chat	Gradient-Based Quantification of Epistemic Uncertainty for Deep Object Detectors	2023	Tobias Riedlinger Matthias Rottmann Marius Schubert Hanno Gottschalk
+	Augmentation by Counterfactual Explanation -Fixing an Overconfident Classifier	2023	Sumedha Singla Nihal Murali Forough Arabshahi Sofia Triantafyllou Kayhan Batmanghelich
+ PDF Chat	Semi-Supervised Object Detection with Uncurated Unlabeled Data for Remote Sensing Images	2024	Nanqing Liu Xun Xu Yingjie Gao Yitao Zhao Heng-Chao Li
+ PDF Chat	Out-of-distribution Detection via Frequency-regularized Generative Models	2023	Mu Cai Yixuan Li

Works Cited by This (35)

Action	Title	Year	Authors
+	TurkerGaze: Crowdsourcing Saliency with Webcam based Eye Tracking	2015	Pingmei Xu Krista A. Ehinger Yinda Zhang Adam Finkelstein Sanjeev R. Kulkarni Jianxiong Xiao
+	Stochastic Backpropagation and Approximate Inference in Deep Generative Models	2014	Danilo Jimenez Rezende Shakir Mohamed Daan Wierstra
+ PDF Chat	Deep neural networks are easily fooled: High confidence predictions for unrecognizable images	2015	Anh‐Tu Nguyen Jason Yosinski Jeff Clune
+	A Learning Algorithm for Boltzmann Machines*	1985	David H. Ackley Geoffrey E. Hinton Terrence J. Sejnowski
+ PDF Chat	Describing Textures in the Wild	2014	Mircea Cimpoi Subhransu Maji Iasonas Kokkinos Sammy Mohamed Andrea Vedaldi
+ PDF Chat	A Family of Nonparametric Density Estimation Algorithms	2012	Esteban G. Tabak Cristina Turner
+	A Theory of Generative ConvNet	2016	Jianwen Xie Yang Lu Song‐Chun Zhu Ying Wu
+	Wide Residual Networks	2016	Sergey Zagoruyko Nikos Komodakis
+	Density estimation using Real NVP	2016	Laurent Dinh Jascha Sohl‐Dickstein Samy Bengio
+	SGDR: Stochastic Gradient Descent with Warm Restarts	2016	Ilya Loshchilov Frank Hutter