Specifically, the upper layer of the HDM serves as a coarse-level policy generator, which utilizes the plan-informed graph attention network (P-GAT) to provide interaction-aware guidance ... which ...

Motivated by the recent success of discrete Ricci curvature in graph neural network (GNNs), we propose TorGNN, an analytic Torsion enhanced Graph Neural Network model. The essential idea is to ...

MGMN consists of a node-graph matching network for effectively learning cross-level interactions between each node of one graph and the other whole graph, and a siamese graph neural network to learn ...

The textbook meaning of an artificial neural network (ANN) is a deep learning model made up of neurons that emulate the structure of the human brain. These neurons are designed to mimic the way nerve ...

Engineering simulations often require significant computational resources and time, which creates barriers for users and can ...

A critical procedure in diagnosing atrial fibrillation is the creation of electro-anatomic activation maps. Current methods generate these mappings from interpolation using a few sparse data points ...

Dataset: The Diabetes dataset contains clinical data and a binary outcome indicating whether a patient has diabetes (Outcome). Quantum Neural Network (QNN): The model is built using a quantum circuit ...

Advanced Artificial Intelligence Theoretical and Computational Chemistry Laboratory, School of Chemistry, University of Hyderabad, Hyderabad, Telangana 500046, India ...

Developed by Meta, PyTorch is a popular machine learning library that helps develop and train neural networks.