Non-Parametric Outlier Synthesis

6 March 2023

Leitian Tao

Papers citing "Non-Parametric Outlier Synthesis"

26 / 76 papers shown

Title
Revisiting Non-separable Binary Classification and its Applications in Anomaly Detection Matthew Lau Ismaila Seck Athanasios P. Meliopoulos Wenke Lee Eugène Ndiaye 25 2 0 03 Dec 2023
Mixture of Gaussian-distributed Prototypes with Generative Modelling for Interpretable and Trustworthy Image Recognition Chong Wang Yuanhong Chen Fengbei Liu Yuyuan Liu Davis J. McCarthy Helen Frazer Gustavo Carneiro 26 1 0 30 Nov 2023
ID-like Prompt Learning for Few-Shot Out-of-Distribution Detection Yichen Bai Zongbo Han Changqing Zhang Bing Cao Xiaoheng Jiang Qinghua Hu OODD 43 18 0 26 Nov 2023
ExCeL : Combined Extreme and Collective Logit Information for Enhancing Out-of-Distribution Detection Naveen Karunanayake Suranga Seneviratne Sanjay Chawla OODD 23 1 0 23 Nov 2023
RankFeat&RankWeight: Rank-1 Feature/Weight Removal for Out-of-distribution Detection Yue Song N. Sebe Wei Wang OODD 38 1 0 23 Nov 2023
NNG-Mix: Improving Semi-supervised Anomaly Detection with Pseudo-anomaly Generation Hao Dong Gaëtan Frusque Yue Zhao Eleni Chatzi Olga Fink AAML 32 5 0 20 Nov 2023
A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning Yiyou Sun Zhenmei Shi Yixuan Li OffRL 40 20 0 06 Nov 2023
Out-of-distribution Detection Learning with Unreliable Out-of-distribution Sources Haotian Zheng Qizhou Wang Zhen Fang Xiaobo Xia Feng Liu Tongliang Liu Bo Han 154 23 0 06 Nov 2023
Learning to Augment Distributions for Out-of-Distribution Detection Qizhou Wang Zhen Fang Yonggang Zhang Feng Liu Yixuan Li Bo Han OODD 30 34 0 03 Nov 2023
On the Powerfulness of Textual Outlier Exposure for Visual OoD Detection Sangha Park J. Mok Dahuin Jung Saehyung Lee Sung-Hoon Yoon 22 10 0 25 Oct 2023
Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation Jianing Zhu Geng Yu Jiangchao Yao Tongliang Liu Gang Niu Masashi Sugiyama Bo Han OODD 34 30 0 21 Oct 2023
Activate and Reject: Towards Safe Domain Generalization under Category Shift Chaoqi Chen Luyao Tang Leitian Tao Hong-Yu Zhou Yue Huang Xiaoguang Han Yizhou Yu OOD 34 10 0 07 Oct 2023
Dream the Impossible: Outlier Imagination with Diffusion Models Xuefeng Du Yiyou Sun Xiaojin Zhu Yixuan Li 25 54 0 23 Sep 2023
Quantile-based Maximum Likelihood Training for Outlier Detection Masoud Taghikhah Nishant Kumar Sinisa Segvic Abouzar Eslami Stefan Gumhold 27 3 0 20 Aug 2023
DIVERSIFY: A General Framework for Time Series Out-of-distribution Detection and Generalization Wang Lu Jindong Wang Xinwei Sun Yiqiang Chen Xiangyang Ji Qiang Yang Xingxu Xie OODD AI4TS 22 15 0 04 Aug 2023
Conservative Prediction via Data-Driven Confidence Minimization Caroline Choi Fahim Tajwar Yoonho Lee Huaxiu Yao Ananya Kumar Chelsea Finn 31 5 0 08 Jun 2023
LoCoOp: Few-Shot Out-of-Distribution Detection via Prompt Learning Atsuyuki Miyai Qing Yu Go Irie Kiyoharu Aizawa OODD 29 64 0 02 Jun 2023
A Survey on Out-of-Distribution Detection in NLP Hao Lang Yinhe Zheng Yixuan Li Jian Sun Feiling Huang Yongbin Li 29 20 0 05 May 2023
AUTO: Adaptive Outlier Optimization for Test-Time OOD Detection Puning Yang Jian Liang Jie Cao Ran He 38 12 0 22 Mar 2023
Mitigating Neural Network Overconfidence with Logit Normalization Hongxin Wei Renchunzi Xie Hao-Ran Cheng Lei Feng Bo An Yixuan Li OODD 163 266 0 19 May 2022
VOS: Learning What You Don't Know by Virtual Outlier Synthesis Xuefeng Du Zhaoning Wang Mu Cai Yixuan Li OODD 178 220 0 02 Feb 2022
Generalized Out-of-Distribution Detection: A Survey Jingkang Yang Kaiyang Zhou Yixuan Li Ziwei Liu 185 879 0 21 Oct 2021
On the Importance of Gradients for Detecting Distributional Shifts in the Wild Rui Huang Andrew Geng Yixuan Li 195 328 0 01 Oct 2021
Noise-robust Graph Learning by Estimating and Leveraging Pairwise Interactions Xuefeng Du Tian Bian Yu Rong Bo Han Tongliang Liu Tingyang Xu Wenbing Huang Yixuan Li Junzhou Huang NoLa 35 11 0 14 Jun 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,661 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015