Jakub Martinka
@jakubmartinka.bsky.social
Ph.D. candidate | Excited about excited states and ⟨QCh|ML⟩ | @heyrovskeho-ustav.bsky.social & @sciencecharles.bsky.social in Prague | https://jakubmartinka.github.io/ | @zeptejsevedce.bsky.social
Reposted by Jakub Martinka
A Descriptor Is All You Need: Accurate Machine Learning of Nonadiabatic Coupling Vectors
#CompChem at J Phys Chem Letters
doi.org/10.1021/acs....
#CompChem at J Phys Chem Letters
doi.org/10.1021/acs....
A Descriptor Is All You Need: Accurate Machine Learning of Nonadiabatic Coupling Vectors
Nonadiabatic couplings (NACs) play a crucial role in modeling photochemical and photophysical processes with methods such as the widely used fewest-switches surface hopping (FSSH). There is, therefore...
doi.org
November 4, 2025 at 6:31 AM
A Descriptor Is All You Need: Accurate Machine Learning of Nonadiabatic Coupling Vectors
#CompChem at J Phys Chem Letters
doi.org/10.1021/acs....
#CompChem at J Phys Chem Letters
doi.org/10.1021/acs....
It was a great pleasure to visit the beautiful city of Toruń for the Molecular Excited States workshop. There were many interesting talks and 𝗲𝘅𝗰𝗶𝘁𝗶𝗻𝗴 discussions. A big thanks to the organisers! #MolEx2025
June 16, 2025 at 10:30 PM
It was a great pleasure to visit the beautiful city of Toruń for the Molecular Excited States workshop. There were many interesting talks and 𝗲𝘅𝗰𝗶𝘁𝗶𝗻𝗴 discussions. A big thanks to the organisers! #MolEx2025
Reposted by Jakub Martinka
A simple approach to rotationally invariant #machine_learning of a vector quantity in #compchem 🧪
doi.org/10.1063/5.02...
doi.org/10.1063/5.02...
A simple approach to rotationally invariant machine learning of a vector quantity
Unlike with the energy, which is a scalar property, machine learning (ML) prediction of vector or tensor properties poses the additional challenge of achieving
doi.org
November 1, 2024 at 1:05 PM
A simple approach to rotationally invariant #machine_learning of a vector quantity in #compchem 🧪
doi.org/10.1063/5.02...
doi.org/10.1063/5.02...