NCBI PubMed Central
open access
GraphMinNet: Learning dependencies in graphs with light complexity minimal architecture.
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
- Reforge: Low-Latency Distributed GNN Serving with Selective Embedding Recomputation#1049613
- Measuring Structure in Graph Benchmark Datasets Using Graph Invariants#1143750
- Structure-Feature Aligned Graph Learning via Alternating Constrained Optimization#363267
- PreGS: A Parameter-Transfer-Based Multi-Expert Graph Neural Network for Node Classification#1062207
- Model-to-Data Distillation for Graph Neural Networks#1144793
Record · ID 625908
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