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On Using Classification Datasets to Evaluate Graph-Level Outlier
  Detection: Peculiar Observations and New Insights
v1v2v3 (latest)

On Using Classification Datasets to Evaluate Graph-Level Outlier Detection: Peculiar Observations and New Insights

Big Data (BD), 2020
23 December 2020
Lingxiao Zhao
Leman Akoglu
ArXiv (abs)PDFHTMLGithub (12★)

Papers citing "On Using Classification Datasets to Evaluate Graph-Level Outlier Detection: Peculiar Observations and New Insights"

46 / 46 papers shown
DeNoise: Learning Robust Graph Representations for Unsupervised Graph-Level Anomaly Detection
DeNoise: Learning Robust Graph Representations for Unsupervised Graph-Level Anomaly Detection
Qingfeng Chen
Haojin Zeng
Jingyi Jie
Shichao Zhang
Debo Cheng
219
0
0
06 Nov 2025
Stealthy Yet Effective: Distribution-Preserving Backdoor Attacks on Graph Classification
Stealthy Yet Effective: Distribution-Preserving Backdoor Attacks on Graph Classification
Xiaobao Wang
Ruoxiao Sun
Yujun Zhang
Bingdao Feng
Dongxiao He
L. Wang
Di Jin
AAML
265
4
0
30 Sep 2025
From Pixels to Graphs: Deep Graph-Level Anomaly Detection on Dermoscopic Images
From Pixels to Graphs: Deep Graph-Level Anomaly Detection on Dermoscopic Images
Dehn Xu
Tim Katzke
Emmanuel Müller
131
1
0
15 Aug 2025
Graph Evidential Learning for Anomaly Detection
Graph Evidential Learning for Anomaly Detection
Chunyu Wei
Wenji Hu
Xingjia Hao
Yunhai Wang
Yueguo Chen
Bing Bai
Haiwei Yang
206
2
0
31 May 2025
Learnable Kernel Density Estimation for Graphs
Learnable Kernel Density Estimation for Graphs
Xudong Wang
Ziheng Sun
Chris Ding
Jicong Fan
507
1
0
27 May 2025
SpectralGap: Graph-Level Out-of-Distribution Detection via Laplacian Eigenvalue Gaps
SpectralGap: Graph-Level Out-of-Distribution Detection via Laplacian Eigenvalue GapsInternational Joint Conference on Artificial Intelligence (IJCAI), 2025
Jiawei Gu
Ziyue Qiao
Zechao Li
399
3
0
21 May 2025
GLADMamba: Unsupervised Graph-Level Anomaly Detection Powered by Selective State Space Model
GLADMamba: Unsupervised Graph-Level Anomaly Detection Powered by Selective State Space Model
Yali Fu
Jindong Li
Zhiqiang Zhang
Qianli Xing
Mamba
622
0
0
23 Mar 2025
Structural Entropy Guided Unsupervised Graph Out-Of-Distribution Detection
Structural Entropy Guided Unsupervised Graph Out-Of-Distribution DetectionAAAI Conference on Artificial Intelligence (AAAI), 2025
Yue Hou
He Zhu
Ruomei Liu
Yingke Su
Jinxiang Xia
Junran Wu
Ke Xu
OODD
610
6
0
13 Mar 2025
Decoupled Graph Energy-based Model for Node Out-of-Distribution Detection on Heterophilic Graphs
Decoupled Graph Energy-based Model for Node Out-of-Distribution Detection on Heterophilic GraphsInternational Conference on Learning Representations (ICLR), 2025
Yuhan Chen
Yihong Luo
Yifan Song
Pengwen Dai
Jing Tang
Xiaochun Cao
OODD
537
10
0
25 Feb 2025
Rethinking Cancer Gene Identification through Graph Anomaly Analysis
Rethinking Cancer Gene Identification through Graph Anomaly AnalysisAAAI Conference on Artificial Intelligence (AAAI), 2024
Yilong Zang
Lingfei Ren
Yongqian Li
Zhikang Wang
David Selby
Zheng Wang
Sebastian Vollmer
Hongzhi Yin
Jiangning Song
Jian Wu
461
3
0
23 Dec 2024
UniGAD: Unifying Multi-level Graph Anomaly Detection
UniGAD: Unifying Multi-level Graph Anomaly DetectionNeural Information Processing Systems (NeurIPS), 2024
Yiqing Lin
Jianheng Tang
Chenyi Zi
Haihong Zhao
Yuan Yao
Jia Li
287
14
0
10 Nov 2024
Rethinking Reconstruction-based Graph-Level Anomaly Detection:
  Limitations and a Simple Remedy
Rethinking Reconstruction-based Graph-Level Anomaly Detection: Limitations and a Simple RemedyNeural Information Processing Systems (NeurIPS), 2024
Sunwoo Kim
Soo Yong Lee
Fanchen Bu
Shinhwan Kang
Kyungho Kim
Jaemin Yoo
Kijung Shin
294
19
0
27 Oct 2024
Graph Pre-Training Models Are Strong Anomaly Detectors
Graph Pre-Training Models Are Strong Anomaly Detectors
Jiashun Cheng
Zinan Zheng
Yang Liu
Jianheng Tang
Jian Shu
Yu Rong
Jia Li
Fugee Tsung
270
3
0
24 Oct 2024
Deep Graph Anomaly Detection: A Survey and New Perspectives
Deep Graph Anomaly Detection: A Survey and New PerspectivesIEEE Transactions on Knowledge and Data Engineering (TKDE), 2024
Hezhe Qiao
Hanghang Tong
Bo An
Irwin King
Charu Aggarwal
Guansong Pang
399
63
0
16 Sep 2024
HGOE: Hybrid External and Internal Graph Outlier Exposure for Graph
  Out-of-Distribution Detection
HGOE: Hybrid External and Internal Graph Outlier Exposure for Graph Out-of-Distribution Detection
Junwei He
Qianqian Xu
Yangbangyan Jiang
Zitai Wang
Yuchen Sun
Qingming Huang
OODD
378
4
0
31 Jul 2024
Motif-Consistent Counterfactuals with Adversarial Refinement for
  Graph-Level Anomaly Detection
Motif-Consistent Counterfactuals with Adversarial Refinement for Graph-Level Anomaly Detection
Chunjing Xiao
Shikang Pang
Wenxin Tai
Yanlong Huang
Goce Trajcevski
Fan Zhou
338
8
0
18 Jul 2024
Imbalanced Graph-Level Anomaly Detection via Counterfactual Augmentation
  and Feature Learning
Imbalanced Graph-Level Anomaly Detection via Counterfactual Augmentation and Feature Learning
Zitong Wang
Xuexiong Luo
Enfeng Song
Qiuqing Bai
Fu Lin
226
2
0
13 Jul 2024
HC-GLAD: Dual Hyperbolic Contrastive Learning for Unsupervised
  Graph-Level Anomaly Detection
HC-GLAD: Dual Hyperbolic Contrastive Learning for Unsupervised Graph-Level Anomaly Detection
Yali Fu
Jindong Li
Jiahong Liu
Qianli Xing
Zhiqiang Zhang
Irwin King
278
5
0
02 Jul 2024
FANFOLD: Graph Normalizing Flows-driven Asymmetric Network for
  Unsupervised Graph-Level Anomaly Detection
FANFOLD: Graph Normalizing Flows-driven Asymmetric Network for Unsupervised Graph-Level Anomaly Detection
Rui Cao
Shijie Xue
Jindong Li
Zhiqiang Zhang
Yi Chang
208
3
0
29 Jun 2024
Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark
Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark
Yili Wang
Yixin Liu
Xu Shen
Chenyu Li
Kaize Ding
Rui Miao
Ying Wang
Shirui Pan
Xin Wang
469
20
0
21 Jun 2024
Safety in Graph Machine Learning: Threats and Safeguards
Safety in Graph Machine Learning: Threats and Safeguards
Song Wang
Yushun Dong
Binchi Zhang
Zihan Chen
Xingbo Fu
Yinhan He
Cong Shen
Chuxu Zhang
Nitesh Chawla
Wenlin Yao
412
11
0
17 May 2024
Anomaly Detection in Graph Structured Data: A Survey
Anomaly Detection in Graph Structured Data: A Survey
Prabin B. Lamichhane
William Eberle
365
12
0
10 May 2024
CVTGAD: Simplified Transformer with Cross-View Attention for
  Unsupervised Graph-level Anomaly Detection
CVTGAD: Simplified Transformer with Cross-View Attention for Unsupervised Graph-level Anomaly Detection
Jindong Li
Qianli Xing
Zhiqiang Zhang
Yi Chang
ViT
232
18
0
03 May 2024
A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD Challenges
A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD ChallengesIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024
Wei Ju
Siyu Yi
Yifan Wang
Zhiping Xiao
Zhengyan Mao
...
Nan Yin
Senzhang Wang
Xinwang Liu
Philip S. Yu
Ming Zhang
AI4CE
427
99
0
07 Mar 2024
FGAD: Self-boosted Knowledge Distillation for An Effective Federated
  Graph Anomaly Detection Framework
FGAD: Self-boosted Knowledge Distillation for An Effective Federated Graph Anomaly Detection Framework
Jinyu Cai
Yunhe Zhang
Zhoumin Lu
Wenzhong Guo
See-kiong Ng
FedML
271
5
0
20 Feb 2024
On the Detection of Reviewer-Author Collusion Rings From Paper Bidding
On the Detection of Reviewer-Author Collusion Rings From Paper Bidding
Steven Jecmen
Nihar B. Shah
Fei Fang
Leman Akoglu
271
13
0
12 Feb 2024
A Hierarchical Framework with Spatio-Temporal Consistency Learning for
  Emergence Detection in Complex Adaptive Systems
A Hierarchical Framework with Spatio-Temporal Consistency Learning for Emergence Detection in Complex Adaptive Systems
Siyuan Chen
Xin Du
Jiahai Wang
416
1
0
18 Jan 2024
ADAMM: Anomaly Detection of Attributed Multi-graphs with Metadata: A
  Unified Neural Network Approach
ADAMM: Anomaly Detection of Attributed Multi-graphs with Metadata: A Unified Neural Network ApproachBigData Congress [Services Society] (BSS), 2023
Konstantinos Sotiropoulos
Lingxiao Zhao
Pierre Jinghong Liang
Leman Akoglu
384
5
0
13 Nov 2023
Towards Self-Interpretable Graph-Level Anomaly Detection
Towards Self-Interpretable Graph-Level Anomaly DetectionNeural Information Processing Systems (NeurIPS), 2023
Yixin Liu
Kaize Ding
Qinghua Lu
Fuyi Li
Leo Yu Zhang
Shirui Pan
357
93
0
25 Oct 2023
SGOOD: Substructure-enhanced Graph-Level Out-of-Distribution Detection
SGOOD: Substructure-enhanced Graph-Level Out-of-Distribution DetectionInternational Conference on Information and Knowledge Management (CIKM), 2023
Zhihao Ding
Jieming Shi
Shiqi Shen
Xuequn Shang
Jiannong Cao
Zhipeng Wang
Zhi Gong
OODDOOD
303
10
0
16 Oct 2023
Self-Discriminative Modeling for Anomalous Graph Detection
Self-Discriminative Modeling for Anomalous Graph Detection
Jinyu Cai
Yunhe Zhang
Jicong Fan
272
15
0
10 Oct 2023
Rayleigh Quotient Graph Neural Networks for Graph-level Anomaly
  Detection
Rayleigh Quotient Graph Neural Networks for Graph-level Anomaly DetectionInternational Conference on Learning Representations (ICLR), 2023
Xiangyu Dong
Xingyi Zhang
Sibo Wang
GNN
475
29
0
04 Oct 2023
Multi-representations Space Separation based Graph-level Anomaly-aware
  Detection
Multi-representations Space Separation based Graph-level Anomaly-aware DetectionInternational Conference on Statistical and Scientific Database Management (SSDBM), 2023
Fu Lin
Haonan Gong
Mingkang Li
Zitong Wang
Yue Zhang
Xuexiong Luo
189
3
0
22 Jul 2023
Graph-level Anomaly Detection via Hierarchical Memory Networks
Graph-level Anomaly Detection via Hierarchical Memory Networks
Chaoxi Niu
Guansong Pang
Ling-Hao Chen
269
29
0
03 Jul 2023
Graph Neural Networks based Log Anomaly Detection and Explanation
Graph Neural Networks based Log Anomaly Detection and Explanation
Zhong Li
Jiayang Shi
M. Leeuwen
515
38
0
02 Jul 2023
Deep Orthogonal Hypersphere Compression for Anomaly Detection
Deep Orthogonal Hypersphere Compression for Anomaly DetectionInternational Conference on Learning Representations (ICLR), 2023
Yunhe Zhang
Yan Sun
Jinyu Cai
Jicong Fan
322
26
0
13 Feb 2023
State of the Art and Potentialities of Graph-level Learning
State of the Art and Potentialities of Graph-level LearningACM Computing Surveys (ACM Comput. Surv.), 2023
Zhenyu Yang
Ge Zhang
Hongzhi Zhang
Jian Yang
Quan.Z Sheng
...
Charu C. Aggarwal
Hao Peng
Wenbin Hu
Edwin R. Hancock
Pietro Lio
GNNAI4CE
355
33
0
14 Jan 2023
GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection
GOOD-D: On Unsupervised Graph Out-Of-Distribution DetectionWeb Search and Data Mining (WSDM), 2022
Yixin Liu
Kaize Ding
Huan Liu
Shirui Pan
277
81
0
08 Nov 2022
Graph Anomaly Detection with Unsupervised GNNs
Graph Anomaly Detection with Unsupervised GNNs
Lingxiao Zhao
Saurabh Sawlani
Arvind Srinivasan
Leman Akoglu
297
24
0
18 Oct 2022
Graph Anomaly Detection with Graph Neural Networks: Current Status and
  Challenges
Graph Anomaly Detection with Graph Neural Networks: Current Status and ChallengesIEEE Access (IEEE Access), 2022
Hwan Kim
Byung Suk Lee
Won-Yong Shin
Sungsu Lim
GNN
312
129
0
29 Sep 2022
BOND: Benchmarking Unsupervised Outlier Node Detection on Static
  Attributed Graphs
BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed GraphsNeural Information Processing Systems (NeurIPS), 2022
Kay Liu
Yingtong Dou
Yue Zhao
Xueying Ding
Xiyang Hu
...
Lichao Sun
Jundong Li
George H. Chen
Zhihao Jia
Philip S. Yu
OOD
447
143
0
21 Jun 2022
Raising the Bar in Graph-level Anomaly Detection
Raising the Bar in Graph-level Anomaly DetectionInternational Joint Conference on Artificial Intelligence (IJCAI), 2022
Chen Qiu
Matthias Kirchler
Stephan Mandt
Maja R. Rudolph
253
78
0
27 May 2022
Deep Graph-level Anomaly Detection by Glocal Knowledge Distillation
Deep Graph-level Anomaly Detection by Glocal Knowledge DistillationWeb Search and Data Mining (WSDM), 2021
Rongrong Ma
Guansong Pang
Ling-Hao Chen
Anton Van Den Hengel
325
122
0
19 Dec 2021
A Comprehensive Survey on Graph Anomaly Detection with Deep Learning
A Comprehensive Survey on Graph Anomaly Detection with Deep LearningIEEE Transactions on Knowledge and Data Engineering (TKDE), 2021
Xiaoxiao Ma
Hongzhi Zhang
Shan Xue
Jian Yang
Chuan Zhou
Quan Z. Sheng
Hui Xiong
Leman Akoglu
GNNAI4TS
510
775
0
14 Jun 2021
Anomaly Mining -- Past, Present and Future
Anomaly Mining -- Past, Present and FutureInternational Joint Conference on Artificial Intelligence (IJCAI), 2021
Leman Akoglu
OODAI4TS
222
12
0
21 May 2021
Anomaly Detection in Large Labeled Multi-Graph Databases
Anomaly Detection in Large Labeled Multi-Graph Databases
Hung T. Nguyen
Pierre Jinghong Liang
Leman Akoglu
342
9
0
07 Oct 2020
1
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