New manual for MLatom@XACS
We are happy to announce that our brand-new manual for MLatom@XACS is now online at http://mlatom.com/manual/. Our …
News
Welcome New Members of Our Group (2022)!
Yuxinxin Chen (master student), Yeyun Chen (co-supervised PhD student) and Yaohuang Huang (research assistant) join our …
A comparative study of different machine learning methods for dissipative quantum dynamics
Recently, Machine Learning (ML) is increasingly used for fast and accurate propagation of quantum dissipative dynamics …
The Newton-X platform for surface hopping and nuclear ensembles
Mario Barbatti, his group and collaborators published an update on Newton-X – a popular open-source platform…
Book “Quantum Chemistry in the Age of Machine Learning”
The book “Quantum Chemistry in the Age of Machine Learning” guides aspiring beginners and specialists in …
Book “Quantum Chemistry in the Age of Machine Learning” Read more →
Tutorial on ML in CECAM school MLQCDyn featuring MLatom@XACS
MLatom@XACS team introduced how to use machine learning in chemistry in the CECAM Machine Learning and Quantum …
Tutorial on ML in CECAM school MLQCDyn featuring MLatom@XACS Read more →
Materials design with MLatom for ammonia separation and storage
We used our MLatom package to develop a machine learning approach for designing materials based on …
Materials design with MLatom for ammonia separation and storage Read more →
One-Shot Trajectory Learning of Open Quantum Systems Dynamics
In the work published in the Journal of Physical Chemistry Letters, we have proposed a one-shot trajectory …
One-Shot Trajectory Learning of Open Quantum Systems Dynamics Read more →
Plenary lecture at ANSCSE25
It has been a great pleasure to give a plenary lecture at the 25th International Annual …
MLatom joins Xiamen Atomistic Computing Suite
We are very happy to announce that MLatom joins Xiamen Atomistic Computing Suite (XACS) which allows …