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physics.chem-ph2025
Molecular Similarity in Machine Learning of Energies in Chemical Reaction Networks
Stefan Gugler, Markus Reiher
Machine learning has emerged as a powerful tool for predicting molecular properties in chemical reaction networks with reduced computational cost. However, accurately predicting en…
physics.chem-ph2022★ 18 cited
Quantum chemical roots of machine-learning molecular similarity descriptors
Stefan Gugler, Markus Reiher
In this work, we explore the quantum chemical foundations of descriptors for molecular similarity. Such descriptors are key for traversing chemical compound space with machine lear…
physics.chem-ph2019★ 63 cited
Gaussian Process-Based Refinement of Dispersion Corrections
Jonny Proppe, Stefan Gugler, Markus Reiher
We employ Gaussian process (GP) regression to adjust for systematic errors in D3-type dispersion corrections introducing the associated, statistically improved model D3-GP. We gene…