Oliver T. Unke
After receiving his Ph.D. in Chemistry from the University of Basel in 2019, Oliver T. Unke became an SNSF postdoctoral research fellow in the Machine Learning Group at Technische Universität Berlin. In 2021, he became a Visiting Researcher at Google and joined Google full time in 2022. His research has focused mainly on developing methods that connect machine learning with quantum chemistry, e.g. for constructing accurate potential energy surfaces and their application in molecular dynamics simulations, or predicting the wave functions of molecules.
Research Areas
Authored Publications
Sort By
Google
Accurate global machine learning force fields for molecules with hundreds of atoms
Stefan Chmiela
Valentin Vassilev Galindo
Adil Kabylda
Huziel E. Sauceda
Alexandre Tkatchenko
Science Advances, 9(2) (2023), eadf0873
So3krates - Self-attention for higher-order geometric interactions on arbitrary length-scales
Thorben Frank
Advances in Neural Information Processing Systems (2022) (to appear)
SE(3)-equivariant prediction of molecular wavefunctions and electronic densities
Mihail Bogojeski
Michael Gastegger
Mario Geiger
Tess Smidt
Advances in Neural Information Processing Systems (2021)
SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects
Stefan Chmiela
Michael Gastegger
Kristof T. Schütt
Huziel Saucceda
Nature Communications, 12 (2021), pp. 7273
