MLatom 3.1.1 is released
We have released the version 3.1.1 of MLatom with improvements in the performance and bug fixes.
Author: Fuchun Ge
Bringing the power of equivariant NN potential through the interface of MACE to MLatom@XACS
Equivariant potentials are the (relatively) new kid on the block with promising high accuracy in published benchmarks. One of them is MACE which we now added to the zoo of machine learning potentials available through the interfaces in MLatom. See …
MLatom 3.1.0 is released
We have released the version 3.1.0 of MLatom with new interface to MACE, one of state-of-the-art machine learning potentials that feature equivariant message passing neural networks.
MLatom 3.0.1 is released
We have released the version 3.0.1 of MLatom with minor upgrades that improve the stability and user experience. In this update, we fixed some bugs in the previous version. Also, we included the docstrings in the code, which might be …
Speeding up quantum dissipative dynamics of open systems with kernel methods
Arif Ullah, Pavlo O. Dral, Speeding up Quantum Dissipative Dynamics of Open Systems with Kernel Methods. New J. Phys. 2021, 23, 113019. DOI: 10.1088/1367-2630/ac3261. Blog post ›
Benchmarking machine learning potentials
Max Pinheiro Jr, Fuchun Ge, Nicolas Ferré, Pavlo O. Dral, Mario Barbatti. Choosing the right molecular machine learning potential. Chem. Sci., 2021, 12, 14396–14413. DOI: 10.1039/D1SC03564A. Blog post › | Tutorial ›