Springer Nature OA
open access
CC BY-NC-ND 4.0
PRA-TAM: prototype-regularised residual affinity maximisation for unsupervised graph anomaly detection
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Generalist Graph Anomaly Detection via Prototype-Based Distillation#792756
- Generalist Graph Anomaly Detection via Prototype-Based Distillation#788756
- RagGAD: Rationale-Aware Conditional Gaussian Mixture Normalizing Flow for Unsupervised Graph Anomaly Detection#617691
- RagGAD: Rationale-Aware Conditional Gaussian Mixture Normalizing Flow for Unsupervised Graph Anomaly Detection#617191
- EGA: ensemble of graph autoencoder for unsupervised anomaly detection#223494
Record · ID 425890
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive