| safe-graph/graph-fraud-detection-papers |
1,148 |
|
0 |
0 |
over 2 years ago |
0 |
|
0 |
|
|
| A curated list of graph-based fraud, anomaly, and outlier detection papers & resources |
| fjchange/awesome-video-anomaly-detection |
330 |
|
0 |
0 |
almost 4 years ago |
0 |
|
1 |
|
|
| Papers for Video Anomaly Detection, released codes collection, Performance Comparision. |
| houssamzenati/Efficient-GAN-Anomaly-Detection |
317 |
|
0 |
0 |
over 5 years ago |
0 |
|
1 |
mit |
Python |
| samet-akcay/skip-ganomaly |
144 |
|
0 |
0 |
about 4 years ago |
0 |
|
21 |
mit |
Python |
| Source code for Skip-GANomaly paper |
| lukasruff/Deep-SVDD |
116 |
|
0 |
0 |
over 7 years ago |
0 |
|
3 |
mit |
Python |
| Repository for the Deep One-Class Classification ICML 2018 paper |
| dgryski/interesting-papers |
112 |
|
0 |
0 |
about 8 years ago |
0 |
|
1 |
|
|
| Interesting papers I'd like to implement (or at least have implementations of) |
| nelson1425/EfficientAD |
92 |
|
0 |
0 |
almost 3 years ago |
0 |
|
0 |
apache-2.0 |
Python |
| Unofficial implementation of EfficientAD https://arxiv.org/abs/2303.14535 |
| orobix/Visual-Feature-Attribution-Using-Wasserstein-GANs-Pytorch |
92 |
|
0 |
0 |
almost 3 years ago |
0 |
|
2 |
mit |
Python |
| Implementation of Visual Feature Attribution using Wasserstein GANs (VAGANs, https://arxiv.org/abs/1711.08998) in PyTorch |
| habedi/PracticalMachineLearning |
79 |
|
0 |
0 |
about 2 years ago |
0 |
|
0 |
bsd-3-clause |
Jupyter Notebook |
| A curated collection of machine learning resources, including notebooks, code, and books, all of which are either free or open-source |
| FelixDJC/Awesome-Graph-Anomaly-Detection |
78 |
|
0 |
0 |
over 2 years ago |
0 |
|
2 |
|
|
| A collection of papers for graph anomaly detection, and published algorithms and datasets. |
