Instant scholar - Falcon: A graph manipulation language for distributed heterogeneous systemsPhD thesis by Unnikrishnan Cheramangalath

A new framework called Falcon, developed by Unnikrishnan Cheramangalath, is revolutionizing graph analytics. This ...

Unlock Hidden Insights with Neo4j and n8n : The Future of Knowledge Graphs

Learn how Neo4j and n8n simplify knowledge graphs for smarter data insights. Build AI-driven graphs for customer data and document navigation ...
IEEE

Enhancing Graph Structure Learning via Motif-Driven Hypergraph Construction

Abstract: Graph neural networks (GNNs), as a cutting-edge technology in deep learning, perform particularly well in various tasks that process graph structure data. However, their foundation on ...
IEEE

Graph Contrastive Learning for Fusion of Graph Structure and Attribute Information

Abstract: Graph Contrastive Learning (GCL) plays a crucial role in multimedia applications due to its effectiveness in analyzing graph-structured data. Existing GCL methods focus on maximizing the ...
C&EN

MODAPro: Explainable Heterogeneous Networks with Variational Graph Autoencoder for Mining Disease-Specific Functional Molecules and Pathways from Omics Data

State Key Laboratory of Medical Proteomics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China University of Chinese Academy of Sciences, Beijing 100049, P.