PINA

PINA has joined the PyTorch Ecosystem, bringing a unified framework for Scientific Machine Learning to researchers and engineers. PINA is an open source Python library built on PyTorch, PyTorch Lightning, and compatible with PyTorch Geometric. It streamlines SciML workflows for modelling physical systems, solving PDEs, building machine learning force fields, simulating dynamics, and more. Its modular structure spans problem definition, model design, solver selection, and training, offering both flexibility and reproducibility. 🔗 Learn more and explore how to get involved: hubs.ly/Q03V4jrL0 #PyTorch #OpenSourceAI #SciML #MachineLearning

@PyTorch We are exited to enter in the ecosystem!

Have a look at the tutorial if interested in #SciML (ROM, Neural PDE Solvers, PINNS) 2/x github.com/mathLab/PINA/b…

We are presenting an extended tutorial on Neural Surrogates at #SIAM MDS 24 1/x linkedin.com/posts/sissamat…

At #ScML in #Strasbourg we promoted our @rozzagroup Research in #machinelearning & #modelreduction, as well as our #computational #webservers @argos_webserver (with @RBniCS) and @atlas_webserver (@fast_computing), our new #opensource #library @PINA_mathLab to solve #PDEs #AI #ML

📌 A recent study by SISSA, published in Nature Scientific Reports, proposes a new approach called GAROM, to simulate complex physical systems by combining #artificialintelligence with reduced order methods. 📄 Press release: sissa.it/news/garom-art…