Machine Learning for Molecular Simulation in Quantum Chemistry
Lead
Dr. Stefan Chmiela
Technische Universität Berlin
Marchstraße 23,
10587
Berlin
Many-Body Dynamics, Physics-Informed Models, Numerical Methods
The Research Training Group of Dr. Stefan Chmiela focuses on developing machine learning methods for molecular simulations, with a special emphasis on many-body problems in quantum chemistry. Modeling many-body problems is computationally intensive due to the rapidly growing number of non-local interactions with system size. In quantum chemistry, even the smallest practical problems already involve enough interacting electrons to render analytical solutions impossible. This combinatorial complexity carries over to the simplified atomistic picture adopted by most empirical models, where a lower number of particles interact. To address this challenge, the group develops methods that combine fundamental principles from computational physics with statistical modeling approaches to foster a better understanding of quantum phenomena in complex systems. This data-driven angle allows questions to be asked in new ways and can give rise to new perspectives on established problems.
Molecular relaxation by reverse diffusion with time step prediction
NeuLat: a toolbox for neural samplers in lattice field theories
Accurate global machine learning force fields for molecules with hundreds of atoms
Photo recap: BIFOLD New Year's reception
At its New Year's reception BIFOLD welcomed a series of distinguished guests and friends from Berlin's AI community.
Photo recap: All Hands Meeting 2023
On October 9 and 10, 2023, BIFOLD welcomed the other Geman AI centers (ScaDS.AI Dresden/Leipzig, Lamarr Institute, Tübingen AI Center, MCML, and the DFKI) in Berlin. The annual meeting featured guests, partners, visitors, and researchers from all over Germany.
AI centers are the foundation of the German AI ecosystem
On October 9th and 10th, 2023, the Berlin Institute for the Foundations of Learning and Data (BIFOLD) at TU Berlin invited scientists from the university AI competence centers (BIFOLD, ScaDS.AI Dresden/Leipzig, Lamarr Institute, Tübingen AI Center, and MCML) and the DFKI to Berlin to present and discuss the latest results of their research on the EUREF campus.