Nature

Electrical and electronic engineering articles from across Nature Portfolio

Electrical and electronic engineering is the branch of engineering that makes use of electricity. Electrical engineering concentrates on systems for generating and transmitting large electrical ...
GitHub

PIML4PDE: Physics-Informed Machine Learning for Solving Partial Differential Equations

The PIML4PDE framework is designed to solve Partial Differential Equations (PDEs) using Physics-Informed Machine Learning (PIML). This framework is intended for educational purposes, demonstrating ...
GitHub

Variational Physic-informed Neural Operator (VINO) for Learning Partial Differential Equations

Solving partial differential equations (PDEs) is a required step in the simulation of natural and engineering systems. The associated computational costs significantly increase when exploring various ...
IEEE

Multi-Task Learning Enhanced Physics-Informed Neural Network for Solving Fluid-Structure Interaction Equations

Abstract: Physics-informed neural networks (PINNs) incorporate physical constraints into their loss functions, allowing them to efficiently solve Partial Differential Equations (PDEs). In this work, ...
IEEE

GPINN: Physics-Informed Neural Network with Graph Embedding

Abstract: Solving partial differential equations (PDEs) is of great importance in numerous fields including physics, engineering, finance, and scientific computing. Physics-Informed Neural Networks ...

Mapping cell development with mathematics-informed machine learning

The development of humans and other animals unfolds gradually over time, with cells taking on specific roles and functions ...