Stefan Heinen - Concepedia

Author

Stefan Heinen

University of Basel ORCID

Also Known As

Heinen, S., Heinen, Stefan, Heinen, Stefan N., Stefan Heinen, Stefan N Heinen

Publications

480

Citations

H-Index

Concepts

All Affiliations

University of Basel Technische Universität Berlin Vector Institute University of Toronto Max Planck Institute for Informatics

About

Stefan Heinen is an author at University of Basel specializing in molecular design, molecular dynamics, and molecular simulation.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	1	1	19
2	Natural Sciences	1	1	19
3	Chemistry	1	1	19
4	Data Science	1	1	19
5	Molecular Sciences	1	1	19

Stefan Heinen

Publications

441

Citations

H-Index

Page 1

	Year	Citations
Machine learning meets volcano plots: computational discovery of cross-coupling catalysts Benjamin Meyer, Boodsarin Sawatlon, Stefan Heinen, Chemical Science	2018	226
Toward the design of chemical reactions: Machine learning barriers of competing mechanisms in reactant space Stefan Heinen, Guido Falk von Rudorff, O. Anatole von Lilienfeld The Journal of Chemical Physics	2021	78
Thousands of reactants and transition states for competing E2 and S N 2 reactions Guido Falk von Rudorff, Stefan Heinen, Marco Bragato, Machine Learning Science and Technology	2020	56
Transition state search and geometry relaxation throughout chemical compound space with quantum machine learning Stefan Heinen, Guido Falk von Rudorff, O. Anatole von Lilienfeld The Journal of Chemical Physics	2022	22
Kernel based quantum machine learning at record rate: Many-body distribution functionals as compact representations Danish Khan, Stefan Heinen, O. Anatole von Lilienfeld The Journal of Chemical Physics EngineeringMachine LearningMany-body Distribution FunctionalsComputational ChemistryChemistry	2023	19
Reducing training data needs with minimal multilevel machine learning (M3L) Stefan Heinen, Danish Khan, Guido Falk von Rudorff, Machine Learning Science and Technology	2024	18
Crash testing machine learning force fields for molecules, materials, and interfaces: molecular dynamics in the TEA challenge 2023 Igor Poltavsky, Mirela Puleva, Anton Charkin-Gorbulin, Chemical Science	2025	12
Crash testing machine learning force fields for molecules, materials, and interfaces: model analysis in the TEA Challenge 2023 Igor Poltavsky, Anton Charkin-Gorbulin, Mirela Puleva, Chemical Science	2025	10

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