126 citations · 301 across the 8 of their papers we have counts for
8 papers
Evaluation of uncertainty estimations for Gaussian process regression based machine learning interatomic potentials
Matthias Holzenkamp, Dongyu Lyu, Ulrich Kleinekathöfer +1
Uncertainty estimations for machine learning interatomic potentials (MLIPs) are crucial for quantifying model error and identifying informative training samples in active learning…
Optimized Multifidelity Machine Learning for Quantum Chemistry
Vivin Vinod, Ulrich Kleinekathöfer, Peter Zaspel
Machine learning (ML) provides access to fast and accurate quantum chemistry (QC) calculations for various properties of interest such as excitation energies. It is often the case…
Multi-Fidelity Machine Learning for Excited State Energies of Molecules
Vivin Vinod, Sayan Maity, Peter Zaspel +1
The accurate but fast calculation of molecular excited states is still a very challenging topic. For many applications, detailed knowledge of the energy funnel in larger molecular…
Time-Dependent Atomistic Simulations of the CP29 Light-Harvesting Complex
Sayan Maity, Pooja Sarngadharan, Vangelis Daskalakis +1
Light harvesting as the first step in photosynthesis is of prime importance for life on earth. For a theoretical description of photochemical processes during light harvesting, spe…
Chebyshev Hierarchical Equations of Motion for Systems with Arbitrary Spectral Densities and Temperatures
Hasan Rahman, Ulrich Kleinekathoefer
The time evolution in open quantum systems, such as a molecular aggregate in contact with a thermal bath, still poses a complex and challenging problem. The influence of the therma…
Coherent laser control of the current through molecular junctions
Guangqi Li, Michael Schreiber, Ulrich Kleinekathoefer
The electron tunneling through a molecular junction modeled by a single site weakly coupled to two leads is studied in the presence of a time-dependent external field using a maste…