עקוב אחר
Claudio Zeni
Claudio Zeni
Senior Researcher @ Microsoft
כתובת אימייל מאומתת בדומיין microsoft.com
כותרת
צוטט על ידי
צוטט על ידי
שנה
Efficient nonparametric -body force fields from machine learning‏
A Glielmo, C Zeni, A De Vita‏
Physical Review B 97 (18), 184307, 2018‏
1642018
A generative model for inorganic materials design‏
C Zeni, R Pinsler, D Zügner, A Fowler, M Horton, X Fu, Z Wang, ...‏
Nature, 1-3, 2025‏
148*2025
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
602018
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
522021
Mattersim: A deep learning atomistic model across elements, temperatures and pressures‏
H Yang, C Hu, Y Zhou, X Liu, Y Shi, J Li, G Li, Z Chen, S Chen, C Zeni, ...‏
arXiv preprint arXiv:2405.04967, 2024‏
472024
On machine learning force fields for metallic nanoparticles‏
C Zeni, K Rossi, A Glielmo, F Baletto‏
Advances in Physics: X 4 (1), 1654919, 2019‏
442019
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), 2022‏
40*2022
Ranking the information content of distance measures‏
A Glielmo, C Zeni, B Cheng, G Csányi, A Laio‏
PNAS nexus 1 (2), pgac039, 2022‏
402022
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
302022
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
222021
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
142020
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 242, 326-352, 2023‏
72023
MatterSim: A Deep Learning Atomistic Model Across Elements‏
H Yang, C Hu, Y Zhou, X Liu, Y Shi, J Li, G Li, Z Chen, S Chen, C Zeni, ...‏
Temperatures and Pressures, 2024‏
62024
Modeling and characterization of the nucleation and growth of carbon nanostructures in physical synthesis‏
K Rossi, GD Förster, C Zeni, J Lam‏
Carbon Trends 11, 100268, 2023‏
42023
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
32024
Gaussian process regression for nonparametric force fields‏
C Zeni‏
King's College London, 2020‏
32020
UniGenX: Unified Generation of Sequence and Structure with Autoregressive Diffusion‏
G Zhang, Y Li, R Luo, P Hu, Z Zhao, L Li, G Liu, Z Wang, R Bi, K Gao, ...‏
arXiv preprint arXiv:2503.06687, 2025‏
2025
King’s Research Portal‏
C Zeni, K Rossi, A Glielmo, A Fekete, N Gaston, FCM Baletto, A De Vita‏
The Journal of Chemical Physics 148, 241739, 2018‏
2018
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
המערכת אינה יכולה לבצע את הפעולה כעת. נסה שוב מאוחר יותר.
מאמרים 1–19