DGraphXinye / DGraphFin_baselineLinks
This is a repository contaning baseline code for DGraphFin Dataset
☆123Updated 2 years ago
Alternatives and similar repositories for DGraphFin_baseline
Users that are interested in DGraphFin_baseline are comparing it to the libraries listed below
Sorting:
- ☆25Updated 2 years ago
- A multi-backend graph learning library.☆240Updated last month
- A Collection for HGNN (Heterogenous Graph Neural Network), including datasets, algorithms and so on.☆59Updated last year
- PyTorch示例代码;复现GNN模型☆133Updated 3 years ago
- GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks☆160Updated 10 months ago
- (WWW 2021) Source code of PC-GNN☆106Updated 3 years ago
- "GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection" in NeurIPS 2023☆132Updated last year
- Bag of Tricks for Graph Neural Networks.☆298Updated last year
- A paper collection about automated graph learning☆97Updated last year
- Awesome literature on imbalanced learning on graphs☆74Updated last year
- Code for CIKM 2020 paper Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters☆282Updated 2 years ago
- Deep Graph Outlier Detection☆66Updated last year
- Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks☆75Updated last year
- ☆80Updated 10 months ago
- The official implementation of the DGA-GNN algorithm.☆26Updated last year
- cs224w(图机器学习)2021冬季课程的colab☆242Updated 4 years ago
- A scalable graph learning toolkit for extremely large graph datasets. (WWW'22, 🏆 Best Student Paper Award)☆155Updated last year
- TKDE'22-GraphCAD: https://arxiv.org/pdf/2108.07516.pdf☆31Updated 2 years ago
- TNNLS: A Synergistic Approach for Graph Anomaly Detection with Pattern Mining and Feature Learning; CIKM'20: Error-bounded Graph Anomaly …☆42Updated 2 years ago
- ☆30Updated 2 years ago
- ☆136Updated last year
- Graph model implementation☆142Updated 3 years ago
- A fundational graph learning framework that solves cross-domain/cross-task classification problems using one model.☆228Updated last year
- Some GNNs are implemented using PyG for node classification tasks, including: GCN, GraphSAGE, SGC, GAT, R-GCN and HAN (Heterogeneous Grap…☆139Updated 2 years ago
- Fraud Detection, Low Homophily, Label Utilization, Graph Mining☆49Updated last year
- "Rethinking Graph Neural Networks for Anomaly Detection" in ICML 2022☆186Updated last year
- [WWW'22] Towards Unsupervised Deep Graph Structure Learning☆143Updated 2 years ago
- ☆38Updated 3 years ago
- ☆117Updated last year
- Revisiting, benchmarking, and refining Heterogeneous Graph Neural Networks.☆330Updated 2 years ago