Colab Notebooks covering deep learning tools for biomolecular structure prediction and design ...

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 ...

Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=5165369 ...

Deep neural networks will allow signal transfer of nerve cells to be analyzed in real time in the future. That is the result ...

The State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, ...

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 ...

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

AI and AR are transforming industrial IoT by enabling real-time data processing, enhancing operational efficiency, and ...

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 ...

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 ...