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05/19/2022
Gold-standard solutions to the Schrödinger equation using deep learning: How much physics do we need?
Finding accurate solutions to the Schrödinger equation is the key unsolv...
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05/18/2021
Solving the electronic Schrödinger equation for multiple nuclear geometries with weight-sharing deep neural networks
Accurate numerical solutions for the Schrödinger equation are of utmost ...
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07/15/2020
Deep Learning for UV Absorption Spectra with SchNarc: First Steps Towards Transferability in Chemical Compound Space
Machine learning (ML) has shown to advance the research field of quantum...
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07/10/2020
Machine learning for electronically excited states of molecules
Electronically excited states of molecules are at the heart of photochem...
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05/28/2020
Machine learning and excited-state molecular dynamics
Machine learning is employed at an increasing rate in the research field...
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02/17/2020
Combining SchNet and SHARC: The SchNarc machine learning approach for excited-state dynamics
In recent years, deep learning has become a part of our everyday life an...
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12/18/2019
Neural networks and kernel ridge regression for excited states dynamics of CH_2NH_2^+: From single-state to multi-state representations and multi-property machine learning mode
Excited-state dynamics simulations are a powerful tool to investigate ph...
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12/18/2018
Molecular Dynamics with Neural-Network Potentials
Molecular dynamics simulations are an important tool for describing the ...
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11/22/2018
Machine learning enables long time scale molecular photodynamics simulations
Photo-induced processes are fundamental in nature, but accurate simulati...
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12/15/2017
