Guansong Pang

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Chunhua ShenZhejiang UniversityVerified email at zju.edu.cn
Longbing CaoDistinguished Chair Professor in AI & ARC Future Fellow (Level 3), Macquarie UniversityVerified email at mq.edu.au
Anton van den HengelDirector of Applied Science at Amazon and Director of the Centre for Augmented Reasoning at AIML.Verified email at adelaide.edu.au
Yu TianHarvard UniversityVerified email at meei.harvard.edu
Gustavo CarneiroProfessor of AI and Machine Learning, University of SurreyVerified email at surrey.ac.uk
Ling Chenuniversity of technology sydneyVerified email at uts.edu.au
Xiao BaiProfessor of Computer Science, Beihang UniversityVerified email at buaa.edu.cn
Cheng YanBeihang UniversityVerified email at buaa.edu.cn
Huan LiuRegents Professor, Arizona State UniversityVerified email at asu.edu
Jianpeng ZhangAlibaba DAMO AcademyVerified email at alibaba-inc.com
Choubo DingThe University of AdelaideVerified email at adelaide.edu.au
yuyuan liuUniversity of AdelaideVerified email at student.adelaide.edu.au
Hongzuo XuNational University of Defense TechnologyVerified email at nudt.edu.cn
Kai Ming TingNanjing UniversityVerified email at nju.edu.cn
Charu AggarwalDistinguished Research Staff Member, IBM T. J. Watson Research CenterVerified email at us.ibm.com
David AlbrechtHead of Digital Technology, John Monash Science SchoolVerified email at monash.edu
Edwin HancockEmeritus Professor, Department of Computer Science, University of York, UKVerified email at cs.york.ac.uk
Christopher LeckieProfessor, Computing and Information Systems, The University of MelbourneVerified email at unimelb.edu.au
Wray BuntineProfessor, VinUniversityVerified email at vinuni.edu.vn
Mahsa SalehiSenior Lecturer, Monash UniversityVerified email at monash.edu

Guansong Pang

Assistant Professor of Computer Science, Singapore Management University

Verified email at smu.edu.sg - Homepage

Machine Learning Data Mining Computer Vision Anomaly Detection Open-world Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Deep Learning for Anomaly Detection: A Review G Pang, C Shen, L Cao, AVD Hengel ACM Computing Surveys (CSUR) 54 (2), 1-38, 2021	1469	2021
Viral Pneumonia Screening on Chest X-rays Using Confidence-Aware Anomaly Detection J Zhang, Y Xie, G Pang, Z Liao, J Verjans, W Li, Z Sun, J He, Y Li, C Shen, ... IEEE Transactions on Medical Imaging, 2020	823*	2020
An improved K-nearest-neighbor algorithm for text categorization S Jiang, G Pang, M Wu, L Kuang Expert Systems with Applications 39 (1), 1503-1509, 2012	390	2012
Deep anomaly detection with deviation networks G Pang, C Shen, A van den Hengel Proceedings of the 25th ACM SIGKDD international conference on knowledge …, 2019	278	2019
Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier Detection G Pang, L Cao, L Chen, H Liu Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018	193	2018
Self-trained Deep Ordinal Regression for End-to-End Video Anomaly Detection G Pang, C Yan, C Shen, A van den Hengel, X Bai Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020	190	2020
Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning Y Tian, G Pang, Y Chen, R Singh, JW Verjans, G Carneiro Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021	182	2021
Beyond triplet loss: person re-identification with fine-grained difference-aware pairwise loss C Yan, G Pang, X Bai, C Liu, X Ning, L Gu, J Zhou IEEE Transactions on Multimedia 24, 1665-1677, 2021	179	2021
Outlier detection in complex categorical data by modelling feature value couplings G Pang, L Cao, L Chen Proceedings of the 25th International Joint Conference on Artificial …, 2016	67	2016
Deep weakly-supervised anomaly detection G Pang, C Shen, H Jin, A van den Hengel Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023	66	2023
Toward deep supervised anomaly detection: Reinforcement learning from partially labeled anomaly data G Pang, A van den Hengel, C Shen, L Cao Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021	66	2021
LeSiNN: Detecting anomalies by identifying least similar nearest neighbours G Pang, KM Ting, D Albrecht 2015 IEEE international conference on data mining workshop (ICDMW), 623-630, 2015	57	2015
Sparse Modeling-based Sequential Ensemble Learning for Effective Outlier Detection in High-dimensional Numeric Data G Pang, L Cao, L Chen, D Lian, H Liu Thirty-Second AAAI Conference on Artificial Intelligence, 2018	56	2018
Deep one-class classification via interpolated gaussian descriptor Y Chen, Y Tian, G Pang, G Carneiro Proceedings of the AAAI Conference on Artificial Intelligence 36 (1), 383-392, 2022	55	2022
Constrained contrastive distribution learning for unsupervised anomaly detection and localisation in medical images Y Tian, G Pang, F Liu, Y Chen, SH Shin, JW Verjans, R Singh, G Carneiro Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021	54	2021
Explainable deep few-shot anomaly detection with deviation networks G Pang, C Ding, C Shen, A Hengel arXiv preprint arXiv:2108.00462, 2021	52	2021
Catching both gray and black swans: Open-set supervised anomaly detection C Ding, G Pang, C Shen Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022	48	2022
Learning Homophily Couplings from Non-IID Data for Joint Feature Selection and Noise-Resilient Outlier Detection G Pang, L Cao, L Chen, H Liu Proceedings of the Twenty-Sixth International Joint Conference on Artificial …, 2017	48	2017
Unsupervised Feature Selection for Outlier Detection by Modelling Hierarchical Value-Feature Couplings G Pang, L Cao, L Chen, H Liu 2016 IEEE 16th International Conference on Data Mining (ICDM-16), 2016	48	2016
CURE: Flexible categorical data representation by hierarchical coupling learning S Jian, G Pang, L Cao, K Lu, H Gao IEEE Transactions on Knowledge and Data Engineering 31 (5), 853-866, 2019	45	2019

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