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Claudio Zeni
Claudio Zeni
Senior Researcher @ Microsoft
Dirección de correo verificada de microsoft.com
Título
Citado por
Citado por
Año
Efficient nonparametric -body force fields from machine learning
A Glielmo, C Zeni, A De Vita
Physical Review B 97 (18), 184307, 2018
1272018
Building machine learning force fields for nanoclusters
C Zeni, K Rossi, A Glielmo, Á Fekete, N Gaston, F Baletto, A De Vita
Journal of Chemical Physics 148 (24), 9, 2018
472018
On machine learning force fields for metallic nanoparticles
C Zeni, K Rossi, A Glielmo, F Baletto
Advances in Physics: X 4 (1), 1654919, 2019
302019
Machine Learning Meets Quantum Physics
A Glielmo, C Zeni, Á Fekete, A De Vita
Schütt, KT, Chmiela, S., von Lilienfeld, OA, Tkatchenko, A., Tsuda, K …, 2020
212020
Data-driven simulation and characterisation of gold nanoparticle melting
C Zeni, K Rossi, T Pavloudis, J Kioseoglou, S de Gironcoli, RE Palmer, ...
Nature Communications 12 (1), 6056, 2021
162021
Compact atomic descriptors enable accurate predictions via linear models
C Zeni, K Rossi, A Glielmo, S De Gironcoli
Journal of Chemical Physics 154 (22), 224112, 2021
122021
Ranking the information content of distance measures
A Glielmo, C Zeni, B Cheng, G Csányi, A Laio
PNAS Nexus 1 (2), pgac039, 2022
92022
Building Nonparametric n-Body Force Fields Using Gaussian Process Regression
A Glielmo, C Zeni, A Fekete, A De Vita
Machine Learning Meets Quantum Physics, 67-98, 2020
92020
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
52022
Gaussian process regression for nonparametric force fields
C Zeni
King's College London, 2020
32020
DADApy: Distance-based analysis of data-manifolds in Python
A Glielmo, I Macocco, D Doimo, M Carli, C Zeni, R Wild, M d’Errico, ...
Patterns 3 (10), 100589, 2022
22022
Structural characterisation of nanoalloys for (photo) catalytic applications with the Sapphire library
RM Jones, K Rossi, C Zeni, M Vanzan, I Vasiljevic, A Santana-Bonilla, ...
Faraday Discussions, 2023
2023
Atomistic fracture modelling by inference-boosted first-principles techniques
A Glielmo, C Zeni, M Caccin, A De Vita
14th International Conference on Fracture, ICF 2017, 2017
2017
King’s Research Portal
KC Mei, N Rubio, PM Coutinho Da Costa, H Kafa, V Abbate, F Festy, ...
Chem. Commun 51, 14981, 2015
2015
Modeling and Characterization of the Nucleation and Growth of Carbon Nanostructures in Physical Synthesis
K Rossi, DG Foerster, C Zeni, J Lam
Available at SSRN 4257420, 0
Young Researcher’s Workshop on Machine Learning for Materials Science
M Todorovic, A Foster, P Rinke, C Zeni, K Rossi, A Glielmo
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–16