IEEE

DeGCN: Deformable Graph Convolutional Networks for Skeleton-Based Action Recognition

Abstract: Graph convolutional networks (GCN) have recently been studied to exploit the graph topology of the human body for skeleton-based action recognition. However, most of these methods ...
IEEE

Topology Identification Using Graph Theory Informed State Estimation-Based Model Selection for Power Distribution Systems

Abstract: This article presents a graph theory-informed approach to state estimation-based model selection for identifying the operational topology of a power distribution system. The proposed method ...
Frontiers

Understanding Graph Isomorphism Network for rs-fMRI Functional Connectivity Analysis

Graph neural networks (GNN) rely on graph operations that include neural network training for various graph related tasks. Recently, several attempts have been made to apply the GNNs to functional ...
GitHub

google-research/talk-like-a-graph

This repository contains code for Talk like a Graph: Encoding Graphs for Large Language Models and Let Your Graph Do the Talking: Encoding Structured Data for LLMs. @inproceedigs{fatemi2024talk, ...
GitHub

GraphGPT: Graph Instruction Tuning for Large Language Models

Data Intelligence Lab@University of Hong Kong, Baidu Inc. This repository hosts the code, data and model weight of GraphGPT (SIGIR'24 full paper track). Due to compatibility issues, if you are using ...