112 citations · 129 across the 6 of their papers we have counts for
7 papers
An ab initio foundation model of wavefunctions that accurately describes chemical bond breaking
Adam Foster, Zeno Schätzle, P. Bernát Szabó +7
Reliable description of bond breaking remains a major challenge for quantum chemistry due to the multireference character of the electronic structure in dissociating species. Multi…
Partitioning the electronic wave function using deep variational Monte Carlo
Matěj Mezera, Paolo A. Erdman, Zeno Schätzle +2
We propose a novel wave function partitioning method that integrates deep-learning variational Monte Carlo with ansätze based on generalized product functions. This approach effect…
Model-free optimization of power/efficiency tradeoffs in quantum thermal machines using reinforcement learning
Paolo Andrea Erdman, Frank Noé
A quantum thermal machine is an open quantum system that enables the conversion between heat and work at the micro or nano-scale. Optimally controlling such out-of-equilibrium syst…
Smooth Normalizing Flows
Jonas Köhler, Andreas Krämer, Frank Noé
Normalizing flows are a promising tool for modeling probability distributions in physical systems. While state-of-the-art flows accurately approximate distributions and energies, a…
Progress in deep Markov State Modeling: Coarse graining and experimental data restraints
Andreas Mardt, Frank Noé
Recent advances in deep learning frameworks have established valuable tools for analyzing the long-timescale behavior of complex systems such as proteins. Especially the inclusion…
Identifying optimal cycles in quantum thermal machines with reinforcement-learning
Paolo Andrea Erdman, Frank Noé
The optimal control of open quantum systems is a challenging task but has a key role in improving existing quantum information processing technologies. We introduce a general frame…
Temperature Steerable Flows and Boltzmann Generators
Manuel Dibak, Leon Klein, Andreas Krämer +1
Boltzmann generators approach the sampling problem in many-body physics by combining a normalizing flow and a statistical reweighting method to generate samples in thermodynamic eq…