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First of all, thank you for the fantastic work you’ve done with PyGOD! It’s an incredibly valuable resource for anomaly detection in graph data, and I truly appreciate the extensive range of tools and models provided.
However, I noticed that currently there are no available models for dynamic (or temporal) graph anomaly detection. Considering the increasing importance of analyzing dynamic graphs, I wanted to ask if there are any plans to support models specifically for dynamic graph anomaly detection in future releases? Any insights or plans in this direction would be much appreciated!
Thank you again for your hard work and this impressive library!
The text was updated successfully, but these errors were encountered:
Thank you for your interest in PyGOD! You are right that, at present, our library only includes detectors for static graphs. We fully agree that dynamic information is critical for graph anomaly detection, and we are indeed plan to expanding our support to dynamic graphs in the long term. However, due to limited resources, we do not yet have a timeline for this feature. Rest assured, we will make every effort to keep the library up to date.
Hi PyGOD team,
First of all, thank you for the fantastic work you’ve done with PyGOD! It’s an incredibly valuable resource for anomaly detection in graph data, and I truly appreciate the extensive range of tools and models provided.
However, I noticed that currently there are no available models for dynamic (or temporal) graph anomaly detection. Considering the increasing importance of analyzing dynamic graphs, I wanted to ask if there are any plans to support models specifically for dynamic graph anomaly detection in future releases? Any insights or plans in this direction would be much appreciated!
Thank you again for your hard work and this impressive library!
The text was updated successfully, but these errors were encountered: