Physicists realize time-varying strong coupling in a magnonic system

Time-varying systems, materials with properties that change over time, have opened new possibilities for the experimental ...
IEEE

Spatio-Temporal Graph Convolutional Neural Networks for Physics-Aware Grid Learning Algorithms

Abstract: This paper proposes novel architectures for spatio-temporal graph convolutional and recurrent neural networks whose structure is inspired by the physics of power systems. The key insight ...
C&EN

Mathematical Modeling of Aβ-42 Dimerization Dynamics: Integrating Physics-Based Simulations, Graph-Based Variational Autoencoder-Driven Neural Relational Inference, and Chaos ...

Computational Biology and Molecular Simulations Laboratory, Department of Biophysics, School of Medicine, Bahçeşehir University, Istanbul 34349, Turkey Lab for Innovative Drugs (Lab4IND), ...
GitHub

cxli233 / FriendsDontLetFriends: Friends don't let friends make certain types of data visualization - What are they and why are they bad.

This is an opinionated essay about good and bad practices in data visualization. Examples and explanations are below. The Scripts/ directory contains .Rmd files that generate the graphics shown below.
IEEE

Physics-Data Hybrid Driven Edge-Featured Graph Attention Networks for Surface Currents Learning of 3D PEC Targets

Abstract: To achieve fast and accurate modeling of electrically large targets, this paper proposes a physics-data hybrid driven surface current learning method (PdEgatSCL), which can learn combined ...