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Effective High-order Graph Representation Learning for Credit Card Fraud Detection

International Joint Conference on Artificial Intelligence (IJCAI), 2024
3 March 2025
Yao Zou
Dawei Cheng
ArXiv (abs)PDFHTML

Papers citing "Effective High-order Graph Representation Learning for Credit Card Fraud Detection"

25 / 25 papers shown
Title
Semi-supervised Credit Card Fraud Detection via Attribute-Driven Graph
  Representation
Semi-supervised Credit Card Fraud Detection via Attribute-Driven Graph RepresentationAAAI Conference on Artificial Intelligence (AAAI), 2023
Sheng Xiang
Mingzhi Zhu
Dawei Cheng
Enxia Li
Ruihui Zhao
Yi Ouyang
Ling Chen
Yefeng Zheng
GNN
196
92
0
24 Dec 2024
Graph Neural Networks for Financial Fraud Detection: A Review
Graph Neural Networks for Financial Fraud Detection: A Review
Dawei Cheng
Yao Zou
Sheng Xiang
Changjun Jiang
AI4TS
216
33
0
01 Nov 2024
Characterizing Graph Datasets for Node Classification:
  Homophily-Heterophily Dichotomy and Beyond
Characterizing Graph Datasets for Node Classification: Homophily-Heterophily Dichotomy and BeyondNeural Information Processing Systems (NeurIPS), 2022
Oleg Platonov
Denis Kuznedelev
Artem Babenko
Liudmila Prokhorenkova
245
56
0
13 Sep 2022
Rethinking Graph Neural Networks for Anomaly Detection
Rethinking Graph Neural Networks for Anomaly DetectionInternational Conference on Machine Learning (ICML), 2022
Jianheng Tang
Jiajin Li
Zi-Chao Gao
Jia Li
201
295
0
31 May 2022
How Powerful are Spectral Graph Neural Networks
How Powerful are Spectral Graph Neural NetworksInternational Conference on Machine Learning (ICML), 2022
Xiyuan Wang
Muhan Zhang
292
276
0
23 May 2022
Tree Decomposed Graph Neural Network
Tree Decomposed Graph Neural NetworkInternational Conference on Information and Knowledge Management (CIKM), 2021
Yu Wang
Hanyu Wang
150
79
0
25 Aug 2021
BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein
  Approximation
BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein ApproximationNeural Information Processing Systems (NeurIPS), 2021
Mingguo He
Zhewei Wei
Zengfeng Huang
Hongteng Xu
318
291
0
21 Jun 2021
AdaGNN: Graph Neural Networks with Adaptive Frequency Response Filter
AdaGNN: Graph Neural Networks with Adaptive Frequency Response FilterInternational Conference on Information and Knowledge Management (CIKM), 2021
Yushun Dong
Kaize Ding
B. Jalaeian
Shuiwang Ji
Jundong Li
209
77
0
26 Apr 2021
Beyond Low-frequency Information in Graph Convolutional Networks
Beyond Low-frequency Information in Graph Convolutional NetworksAAAI Conference on Artificial Intelligence (AAAI), 2021
Deyu Bo
Xiao Wang
C. Shi
Huawei Shen
GNN
354
691
0
04 Jan 2021
Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged
  Fraudsters
Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters
Yingtong Dou
Zhiwei Liu
Li Sun
Yutong Deng
Hao Peng
Philip S. Yu
AAML
212
579
0
19 Aug 2020
Adaptive Universal Generalized PageRank Graph Neural Network
Adaptive Universal Generalized PageRank Graph Neural NetworkInternational Conference on Learning Representations (ICLR), 2020
Eli Chien
Jianhao Peng
Pan Li
O. Milenkovic
916
903
0
14 Jun 2020
Graph Random Neural Network for Semi-Supervised Learning on Graphs
Graph Random Neural Network for Semi-Supervised Learning on Graphs
Wenzheng Feng
Jie Zhang
Yuxiao Dong
Yu Han
Huanbo Luan
Qian Xu
Qiang Yang
Evgeny Kharlamov
Jie Tang
350
458
0
22 May 2020
Alleviating the Inconsistency Problem of Applying Graph Neural Network
  to Fraud Detection
Alleviating the Inconsistency Problem of Applying Graph Neural Network to Fraud DetectionAnnual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2020
Zhiwei Liu
Yingtong Dou
Philip S. Yu
Yutong Deng
Hao Peng
GNN
240
334
0
01 May 2020
A Semi-supervised Graph Attentive Network for Financial Fraud Detection
A Semi-supervised Graph Attentive Network for Financial Fraud DetectionIndustrial Conference on Data Mining (IDM), 2019
Daixin Wang
J. Lin
Peng Cui
Quanhui Jia
Zhen Wang
Yanming Fang
Quan Yu
Jun Zhou
Shuang Yang
Yuan Qi
GNN
154
407
0
28 Feb 2020
Heterogeneous Graph Neural Networks for Malicious Account Detection
Heterogeneous Graph Neural Networks for Malicious Account DetectionInternational Conference on Information and Knowledge Management (CIKM), 2018
Ziqi Liu
Chaochao Chen
Xinxing Yang
Jun Zhou
Xiaolong Li
Le Song
165
384
0
27 Feb 2020
Geom-GCN: Geometric Graph Convolutional Networks
Geom-GCN: Geometric Graph Convolutional NetworksInternational Conference on Learning Representations (ICLR), 2020
Hongbin Pei
Bingzhen Wei
Kevin Chen-Chuan Chang
Yu Lei
Bo Yang
GNN
611
1,326
0
13 Feb 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library
PyTorch: An Imperative Style, High-Performance Deep Learning LibraryNeural Information Processing Systems (NeurIPS), 2019
Adam Paszke
Sam Gross
Francisco Massa
Adam Lerer
James Bradbury
...
Sasank Chilamkurthy
Benoit Steiner
Lu Fang
Junjie Bai
Soumith Chintala
ODL
940
48,028
0
03 Dec 2019
DeepGCNs: Can GCNs Go as Deep as CNNs?
DeepGCNs: Can GCNs Go as Deep as CNNs?
Ge Li
Matthias Muller
Ali K. Thabet
Guohao Li
3DPCGNN
381
1,490
0
07 Apr 2019
Representation Learning on Graphs with Jumping Knowledge Networks
Representation Learning on Graphs with Jumping Knowledge Networks
Keyulu Xu
Chengtao Li
Yonglong Tian
Tomohiro Sonobe
Ken-ichi Kawarabayashi
Stefanie Jegelka
GNN
752
2,219
0
09 Jun 2018
Deeper Insights into Graph Convolutional Networks for Semi-Supervised
  Learning
Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning
Qimai Li
Zhichao Han
Xiao-Ming Wu
GNNSSL
476
3,127
0
22 Jan 2018
Graph Attention Networks
Graph Attention NetworksInternational Conference on Learning Representations (ICLR), 2017
Petar Velickovic
Guillem Cucurull
Arantxa Casanova
Adriana Romero
Pietro Lio
Yoshua Bengio
GNN
1.9K
23,602
0
30 Oct 2017
Inductive Representation Learning on Large Graphs
Inductive Representation Learning on Large GraphsNeural Information Processing Systems (NeurIPS), 2017
William L. Hamilton
Z. Ying
J. Leskovec
1.5K
17,742
0
07 Jun 2017
Semi-Supervised Classification with Graph Convolutional Networks
Semi-Supervised Classification with Graph Convolutional Networks
Thomas Kipf
Max Welling
GNNSSL
1.7K
32,431
0
09 Sep 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
3.6K
214,438
0
10 Dec 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic OptimizationInternational Conference on Learning Representations (ICLR), 2014
Diederik P. Kingma
Jimmy Ba
ODL
4.5K
160,277
0
22 Dec 2014
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