This document serves as user manual for HydraGNN, a scalable graph neural network (GNN) architecture that allows for a simultaneous prediction of multiple target properties using multi-task learning ...
Abstract This lecture is designed for Week 9 of the MH1301 Discrete Mathematics curriculum, transitioning from graph traversals to structural properties. We will define the chromatic number and ...
Abstract: This paper investigates a GraphRAG framework that integrates knowledge graphs into the Retrieval-Augmented Generation (RAG) architecture to enhance networking applications. While RAG has ...
Abstract: Graph problems are common across many fields, from scientific computing to social sciences. Despite their importance and the attention received, implementing graph algorithms effectively on ...
Imagine having your AI assistant in Cursor seamlessly trigger complex GitHub workflows—fetching issue details, analyzing commit history, and creating professional pull requests—all through natural ...
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