A new technical paper titled “Massively parallel and universal approximation of nonlinear functions using diffractive processors” was published by researchers at UCLA. “Nonlinear computation is ...

Researchers at the University of California, Los Angeles (UCLA) have developed an optical computing framework that performs large-scale nonlinear computations using linear materials. Reported in ...

Victor Lee is director of product management at TigerGraph. Graph databases excel at answering complex questions about relationships in large data sets. But they hit a wall—in terms of both ...

Abstract: Converting relational data into a property graph is advantageous for relational data analysis using graph algorithms. However, existing methods for constructing property graphs from ...

This repository contains the implementation of the paper "An Intelligent Anycast Routing Method Integrating Software-Defined Networking and Parallel Hierarchical Graph Reinforcement Learning." The ...

Abstract: Modern shared-memory parallel programming models, such as OpenMP and Cilk, enable developers to encode a parallel execution plan within their code. Existing compilers, including Clang and ...

This repository contains the implementation of AutoSchemaKG, a novel framework for automatic knowledge graph construction that combines schema generation via conceptualization. The framework is ...