As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

Abstract: Vision Graph Neural Network (ViG) is the first graph neural network model capable of directly processing image data. The community primarily focuses on the model structures to improve ViG’s ...

Learn how backpropagation works by building it from scratch in Python! This tutorial explains the math, logic, and coding behind training a neural network, helping you truly understand how deep ...

Abstract: In this letter, we propose a meta-learning-based fast adversarial training method to address the vulnerability of graph neural network (GNN) based resource allocation method to adversarial ...

Department of Materials Science and Engineering, Indian Institute of Technology, Delhi-110016, India Department of Chemistry, Indian Institute of Technology, Delhi-110016, India ...

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jcim.5c01525. Efficiency analysis of different normalization strategies ...

PyTorch Geometric Signed Directed is a signed/directed graph neural network extension library for PyTorch Geometric. The paper is accepted by LoG 2023.