495 citations · 538 across the 7 of their papers we have counts for
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Enabling ab initio geometry optimization of strongly correlated systems with transferable deep quantum Monte Carlo
P. Bernát Szabó, Zeno Schätzle, Frank Noé
A faithful description of chemical processes requires exploring extended regions of the molecular potential energy surface (PES), which remains challenging for strongly correlated…
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…
Deep quantum Monte Carlo approach for polaritonic chemistry
Yifan Tang, Gian Marcello Andolina, Alica Cuzzocrea +5
Recent years have witnessed a surge of experimental and theoretical interest in controlling the properties of matter, such as its chemical reactivity, by confining it in optical ca…
Highly Accurate Real-space Electron Densities with Neural Networks
Lixue Cheng, P. Bernát Szabó, Zeno Schätzle +7
Variational ab-initio methods in quantum chemistry stand out among other methods in providing direct access to the wave function. This allows in principle straightforward extractio…
An improved penalty-based excited-state variational Monte Carlo approach with deep-learning ansatzes
P. Bernát Szabó, Zeno Schätzle, Mike T. Entwistle +1
We introduce several improvements to the penalty-based variational quantum Monte Carlo (VMC) algorithm for computing electronic excited states of Entwistle [M. T.…