← authors · overview

• Machine learning for electronically excited states of molecules
  2020 · 383 citations
• NQCDynamics.jl: A Julia Package for Nonadiabatic Quantum Classical Molecular Dynamics in the Condensed Phase
  2022 · 22 citations
• Incorporating Long-Range Interactions via the Multipole Expansion into Ground and Excited-State Molecular Simulations
  2025 · 5 citations
• Machine learning enables long time scale molecular photodynamics simulations
  2018
• Neural networks and kernel ridge regression for excited states dynamics of CH$_2$NH$_2^+$: From single-state to multi-state representations and multi-property machine learning models
  2019
• Combining SchNet and SHARC: The SchNarc machine learning approach for excited-state dynamics
  2020
• Machine learning and excited-state molecular dynamics
  2020
• Deep Learning for UV Absorption Spectra with SchNarc: First Steps Towards Transferability in Chemical Compound Space
  2020
• Perspective on integrating machine learning into computational chemistry and materials science
  2021
• BuRNN: Buffer Region Neural Network Approach for Polarizable-Embedding Neural Network / Molecular Mechanics Simulations
  2021