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most citedA Kernel-based Machine Learning Approach to Computing Quasiparticle Energies within Many-Body Green's Functions Theory

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physics.comp-ph2020★ 1 cited

A Kernel-based Machine Learning Approach to Computing Quasiparticle Energies within Many-Body Green's Functions Theory

Gianluca Tirimbó, Onur Çaylak, Björn Baumeier

We present a Kernel Ridge Regression (KRR) based supervised learning method combined with Genetic Algorithms (GAs) for the calculation of quasiparticle energies within Many-Body Gr…

physics.comp-ph2018

Electronic Excitations in Complex Molecular Environments: Many-Body Green's Functions Theory in VOTCA-XTP

Jens Wehner, Lothar Brombacher, Joshua Brown +6

Many-body Green's functions theory within the GW approximation and the Bethe-Salpeter Equation (BSE) is implemented in the open-source VOTCA-XTP software, aiming at the calculation…