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Alexandre Tkatchenko — most-cited papers & profile · AI for Science
← authors
·
overview
Alexandre Tkatchenko
19
papers ·
1538
citations ·
82
h-index
University of Luxembourg
Google Scholar ↗
Semantic Scholar ↗
OpenAlex ↗
Most-cited papers
Towards Exact Molecular Dynamics Simulations with Machine-Learned Force Fields
2018 · 673 citations
SchNet: A continuous-filter convolutional neural network for modeling quantum interactions
2017 · 470 citations
Machine learning force fields and coarse-grained variables in molecular dynamics: application to materials and biological systems
2020 · 230 citations
QM7-X: A comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules
2020 · 122 citations
Accurate Machine Learned Quantum-Mechanical Force Fields for Biomolecular Simulations
2022 · 17 citations
Accurate global machine learning force fields for molecules with hundreds of atoms
2022 · 9 citations
Force Field Analysis Software and Tools (FFAST): Assessing Machine Learning Force Fields Under the Microscope
2023 · 9 citations
SchNet - a deep learning architecture for molecules and materials
2017 · 2 citations
Learning representations of molecules and materials with atomistic neural networks
2018 · 2 citations
Towards Linearly Scaling and Chemically Accurate Global Machine Learning Force Fields for Large Molecules
2022 · 1 citations
Non-covalent interactions across organic and biological subsets of chemical space: Physics-based potentials parametrized from machine learning
2017 · 1 citations
BIGDML: Towards Exact Machine Learning Force Fields for Materials
2021 · 1 citations
A Journey with THeSeuSS: Automated Python Tool for Modeling IR and Raman Vibrational Spectra of Molecules and Solids
2024 · 1 citations
AI4X Roadmap: Artificial Intelligence for the advancement of scientific pursuit and its future directions
2025
aims-PAX: Parallel Active eXploration for the automated construction of Machine Learning Force Fields
2025
Top co-authors
Klaus-Robert M\"uller
· 8
Huziel E. Sauceda
· 5
Stefan Chmiela
· 5
Adil Kabylda
· 4
Igor Poltavsky
· 3
Kristof T. Sch\"utt
· 3
Alessio Fallani
· 2
Leonardo Medrano Sandonas
· 2
Oliver T. Unke
· 2
Robert A. DiStasio Jr
· 2
Valentin Vassilev-Galindo
· 2
Aaron R. Dinner
· 1
Topics
Chemistry
Materials
Physics ML
Drug Discovery
Climate & Weather
Protein Science
Medical AI