Abstract: Attributed graph clustering is of significance for an in-depth understanding of the intrinsic organization of complex networks. Recently, owing to the powerful learning capability of deep ...

Abstract: Graphs are naturally used to describe the structures of various real-world systems in biology, society, computer science etc., where subgraphs or motifs as basic blocks play an important ...

Sub-headline: HUST researchers systematize SNA methods, building an evolutionary taxonomy based on graph representation ...

Validated AI retrosynthesis, now native to the agent-native chemistry OS—so every proposed route arrives inspectable ...

July 2, 2026 A pioneering climate scientist is challenging a U.S. government report that cited his research while reaching what he says is the exact opposite conclusion. Benjamin Santer and his ...

Sudhir Hasbe, Neo4j's President and Chief Product Officer, on the strategic shift behind the GraphAware deal, what "open ...

Mathematicians proved in the early 1990s that randomly connecting routers produces the most efficient, resilient network topology. It took AWS roughly 30 years to turn that result into production ...

A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted ...

We benchmark on the community-standard Dalke NN dataset (1,000 high-similarity ChEMBL pairs) — the same dataset widely used by RDKit, CDK, and the academic MCS literature. Identical SMILES input, same ...

Discover how Vimal Teja Manne is advancing the future of digital payments through strategic leadership, payment innovation, ...

This International Women’s Day article highlights pioneering women in engineering, science, computing, and space whose work ...