2 citations · 4 across the 2 of their papers we have counts for
3 papers
Transferable Water Potentials Using Equivariant Neural Networks
Tristan Maxson, Tibor Szilvasi
Machine learning interatomic potentials (MLIPs) are an emerging modeling technique that promises to provide electronic structure theory accuracy for a fraction of its cost, however…
Enhancing the Quality and Reliability of Machine Learning Interatomic Potentials through Better Reporting Practices
Tristan Maxson, Ademola Soyemi, Benjamin W. J. Chen +1
Recent developments in machine learning interatomic potentials (MLIPs) have empowered even non-experts in machine learning to train MLIPs for accelerating materials simulations. Ho…
GPAW: An open Python package for electronic-structure calculations
Jens Jørgen Mortensen, Ask Hjorth Larsen, Mikael Kuisma +44
We review the GPAW open-source Python package for electronic structure calculations. GPAW is based on the projector-augmented wave method and can solve the self-consistent density…