Abstract: In this study, physics-informed graph residual learning (PhiGRL) is proposed as an effective and robust deep learning (DL)-based approach for 3-D electromagnetic (EM) modeling. Extended from ...

This repo is the official implementation of "PhyGNNet: Solving spatiotemporal PDEs with Physics-informed Graph Neural Network" by Longxiang Jiang, Liyuan Wang, Xinkun Chu, Yonghao Xiao, and Hao Zhang ...

Abstract: The solving of nonlinear equation systems (e.g., complex transcendental dispersion equation systems in waveguide systems) is a fundamental topic in science and engineering. Davidenko method ...

For most Class 12 students, Mathematics is the subject that decides their mood during board exams. Some enjoy the challenge, ...

This repository contains both Jupyter notebooks for solving a link prediction problem using Neo4j’s Graph Data Science Library and scikit-learn. The associated ...

A logarithm is the power which a certain number is raised to get another number. Before calculators and various types of complex computers were invented it was difficult for scientists and ...

Karthik Ramgopal and Daniel Hewlett discuss the evolution of AI at LinkedIn, from simple prompt chains to a sophisticated ...

🦞 Scores of dead lobsters 🌧️ Photos: San Diego flooding 🍋 2026 bucket list 🗳️ News to watch in ’26 📈 Business stories to watch in '26 ...

Learn how the Least Squares Criterion determines the line of best fit for data analysis, enhancing predictive accuracy in finance, economics, and investing.