Nature

Physics-Informed Machine Learning for Personalized Disease Prediction, Prevention, and Management

This Collection supports and amplifies research related to SDG3, SDG9 and SDG10. Physics-Informed Machine Learning (PI-ML) combines principles from physics- and biology-based modeling with data-driven ...
Nanowerk

Ultra-robust machine-learning models capable of stable molecular simulations at extreme temperatures

Researchers have created a groundbreaking physics?informed machine?learning model that can run molecular simulations for ...
Fabbaloo

PiGRAND Brings Physics Informed Graph Diffusion To AM

A new research model called PiGRAND merges physics guidance with graph neural diffusion to predict and control AM processes.
EurekAlert!

Transfer learning-enhanced physics-informed neural network (TLE-PINN): A breakthrough in melt pool prediction for laser melting

The TLE-PINN method integrates EPINN and deep learning models through a transfer learning framework, combining strong physical constraints and efficient computational capabilities to accurately ...
NPR

Nobel Prize in physics awarded to 2 scientists for discoveries in machine learning

STOCKHOLM — John Hopfield and Geoffrey Hinton were awarded the Nobel Prize in physics Tuesday for discoveries and inventions that formed the building blocks of machine learning. "This year's two Nobel ...