Learning embeddings for entities and relations in knowledge graph (KG) have benefited many downstream tasks. In recent years, scoring functions, the crux of KG learning, have been human designed to ...

Many graph-based algorithms in high performance computing (HPC) use approximate solutions due to having algorithms that are computationally expensive or serial in nature. Neural acceleration, i.e., ...

TySON (TypeScript Object Notation) is a subset of TypeScript, chosen to be useful as an embeddable configuration language that generates JSON. You can think of TySON as JSON + comments + types + basic ...

This is the official pytorch implementation of the paper "ML-GOOD: Towards Multi-Label Graph Out-Of-Distribution Detection, AAAI2025". Also, we provide an appendix here.

Graphene, serving as electrodes, is widely applied in electronic and optoelectronic devices. Work function as one of the fundamental intrinsic characteristics of graphene directly affects the ...

It will be useful to regulate AI, but primarily at the application level. For example, AI applications to medical diagnosis should be regulated very differently from AI applications to self-driving ...