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Andrea Anelli
Andrea Anelli
Digital Drug Development @ Roche
Verified email at roche.com
Title
Cited by
Cited by
Year
Automatic selection of atomic fingerprints and reference configurations for machine-learning potentials
G Imbalzano, A Anelli, D Giofré, S Klees, J Behler, M Ceriotti
The Journal of chemical physics 148 (24), 2018
3512018
Learning the electronic density of states in condensed matter
C Ben Mahmoud, A Anelli, G Csányi, M Ceriotti
Physical Review B 102 (23), 235130, 2020
1172020
Mapping uncharted territory in ice from zeolite networks to ice structures
EA Engel, A Anelli, M Ceriotti, CJ Pickard, RJ Needs
Nature communications 9 (1), 2173, 2018
792018
A Bayesian approach to NMR crystal structure determination
EA Engel, A Anelli, A Hofstetter, F Paruzzo, L Emsley, M Ceriotti
Physical Chemistry Chemical Physics 21 (42), 23385-23400, 2019
572019
Generalized Convex Hull Construction for Materials Discovery
A Anelli, EA Engel, CJ Pickard, M Ceriotti
Physical Review Materials 2, 103804, 2018
472018
Exploring the robust extrapolation of high-dimensional machine learning potentials
C Zeni, A Anelli, A Glielmo, K Rossi
Physical Review B 105 (16), 165141, 2022
312022
The seventh blind test of crystal structure prediction: structure generation methods
LM Hunnisett, J Nyman, N Francia, NS Abraham, CS Adjiman, ...
Structural Science 80 (6), 2024
192024
The seventh blind test of crystal structure prediction: structure ranking methods
LM Hunnisett, N Francia, J Nyman, NS Abraham, S Aitipamula, T Alkhidir, ...
Structural Science 80 (6), 2024
152024
Comparative Analysis of Chemical Descriptors by Machine Learning Reveals Atomistic Insights into Solute–Lipid Interactions
JJ Lange, A Anelli, J Alsenz, M Kuentz, PJ O’Dwyer, W Saal, ...
Molecular pharmaceutics 21 (7), 3343-3355, 2024
52024
Divide-and-conquer potentials enable scalable and accurate predictions of forces and energies in atomistic systems
C Zeni, A Anelli, A Glielmo, S de Gironcoli, K Rossi
Digital Discovery 3 (1), 113-121, 2024
42024
Geometric deep learning-guided Suzuki reaction conditions assessment for applications in medicinal chemistry
K Atz, DF Nippa, AT Müller, V Jost, A Anelli, M Reutlinger, C Kramer, ...
RSC Medicinal Chemistry 15 (7), 2310-2321, 2024
32024
Robust and efficient reranking in crystal structure prediction: a data driven method for real-life molecules
A Anelli, H Dietrich, P Ectors, F Stowasser, T Bereau, M Neumann, ...
CrystEngComm 26 (41), 5845-5849, 2024
22024
Automatic solid form classification in pharmaceutical drug development
J Lange, L Komissarov, R Lang, DD Enkelmann, A Anelli
AI for Accelerated Materials Discovery (AI4MAT) NeurIPS 2024 Workshop, 2024
12024
Integrating machine learning in crystal structure prediction for pharmaceutical compounds
A Anelli, H Dietrich, P Ectors, F Stowasser, T Bereau, M Neumann, ...
ACTA CRYSTALLOGRAPHICA A-FOUNDATION AND ADVANCES 78, E673-E673, 2022
2022
Machine learning potentials always extrapolate, it does not matter.
C Zeni, A Anelli, A Glielmo, K Rossi
arXiv e-prints, arXiv: 2112.10434, 2021
2021
Characterising Structure and Stability of Materials using Machine Learning
A Anelli
EPFL, 2020
2020
MS28-1-11 Integrating machine learning in crystal structure prediction for pharmaceutical compounds# MS28-1-11
A Anelli, H Dietrich, P Ectors, F Stowasser, T Bereau, M Neumann, ...
Foundations of Crystallography, 0
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