We propose an approximated mixed-integer quadratically constrained program (MIQCP) to model dynamic reconfiguration, along with a pioneering formulation for voltage regulator (VR) tap-setting based on ...

In the past, graph neural networks (GNNs) have shown promise in capturing the non-Euclidean ... aspects from classification and regression tasks to interpretation tasks. STIGR leverages a dynamic ...

NetworKit is a growing open-source toolkit for large-scale network analysis.

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

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

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 Artificial Neural Network market was USD 248M in 2023 and is expected to reach USD 1256M by 2032, growing at a 19.79% CAGR from 2024 to 2032.

A dual array system model with flexible specimen connections is established, and this system is identified using the LSTM neural network. The LSTM neural network was validated for identifying the dual ...

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 ...