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Michele Ceriotti
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2020 – today
- 2024
- [j12]Matthias Kellner
, Michele Ceriotti
Uncertainty quantification by direct propagation of shallow ensembles. Mach. Learn. Sci. Technol. 5(3): 35006 (2024) - [j11]Marcel F. Langer
Probing the effects of broken symmetries in machine learning. Mach. Learn. Sci. Technol. 5(4): 04 (2024) - [j10]Filippo Bigi
A prediction rigidity formalism for low-cost uncertainties in trained neural networks. Mach. Learn. Sci. Technol. 5(4): 45018 (2024) - [i17]Filippo Bigi, Sanggyu Chong, Michele Ceriotti, Federico Grasselli:
A prediction rigidity formalism for low-cost uncertainties in trained neural networks. CoRR abs/2403.02251 (2024) - [i16]Marcel F. Langer, Sergey N. Pozdnyakov, Michele Ceriotti:
Probing the effects of broken symmetries in machine learning. CoRR abs/2406.17747 (2024) - [i15]Beatriz Borges, Negar Foroutan, Deniz Bayazit, Anna Sotnikova, Syrielle Montariol, Tanya Nazaretzky, Mohammadreza Banaei, Alireza Sakhaeirad, Philippe Servant, Seyed Parsa Neshaei, Jibril Frej, Angelika Romanou, Gail Weiss, Sepideh Mamooler, Zeming Chen, Simin Fan, Silin Gao, Mete Ismayilzada, Debjit Paul, Alexandre Schöpfer, Andrej Janchevski, Anja Tiede, Clarence Linden, Emanuele Troiani, Francesco Salvi, Freya Behrens, Giacomo Orsi
Could ChatGPT get an Engineering Degree? Evaluating Higher Education Vulnerability to AI Assistants. CoRR abs/2408.11841 (2024) - 2023
- [c2]Sergey Pozdnyakov, Michele Ceriotti:
Smooth, exact rotational symmetrization for deep learning on point clouds. NeurIPS 2023 - [i14]Filippo Bigi, Michele Ceriotti:
Fast evaluation of real spherical harmonics and their derivatives in Cartesian coordinates. CoRR abs/2302.08381 (2023) - [i13]Jigyasa Nigam, Sergey N. Pozdnyakov, Kevin K. Huguenin-Dumittan, Michele Ceriotti:
Completeness of Atomic Structure Representations. CoRR abs/2302.14770 (2023) - [i12]Filippo Bigi, Sergey N. Pozdnyakov, Michele Ceriotti:
Wigner kernels: body-ordered equivariant machine learning without a basis. CoRR abs/2303.04124 (2023) - [i11]Sergey N. Pozdnyakov, Michele Ceriotti:
Smooth, exact rotational symmetrization for deep learning on point clouds. CoRR abs/2305.19302 (2023) - [i10]Kevin K. Huguenin-Dumittan, Philip Loche, Haoran Ni, Michele Ceriotti:
Physics-inspired Equivariant Descriptors of Non-bonded Interactions. CoRR abs/2308.13208 (2023) - [i9]Edoardo Cignoni, Divya Suman, Jigyasa Nigam, Lorenzo Cupellini, Benedetta Mennucci, Michele Ceriotti:
Electronic excited states from physically-constrained machine learning. CoRR abs/2311.00844 (2023) - 2022
- [j9]Sergey N. Pozdnyakov
Incompleteness of graph neural networks for points clouds in three dimensions. Mach. Learn. Sci. Technol. 3(4): 45020 (2022) - [i8]Sergey N. Pozdnyakov, Michele Ceriotti:
Incompleteness of graph convolutional neural networks for points clouds in three dimensions. CoRR abs/2201.07136 (2022) - [i7]Jigyasa Nigam, Guillaume Fraux, Michele Ceriotti:
Unified theory of atom-centered representations and graph convolutional machine-learning schemes. CoRR abs/2202.01566 (2022) - [i6]Chiheb Ben Mahmoud, Federico Grasselli
Predicting hot electrons free energies from ground-state data. CoRR abs/2205.05591 (2022) - [i5]Filippo Bigi, Kevin Huguenin-Dumittan, Michele Ceriotti, David E. Manolopoulos:
A smooth basis for atomistic machine learning. CoRR abs/2209.01948 (2022) - 2021
- [j8]Alexander Goscinski
The role of feature space in atomistic learning. Mach. Learn. Sci. Technol. 2(2): 25028 (2021) - [j7]Rose K. Cersonsky, Benjamin A. Helfrecht
Improving sample and feature selection with principal covariates regression. Mach. Learn. Sci. Technol. 2(3): 35038 (2021) - [i4]Alexander Goscinski, Felix Musil, Sergey Pozdnyakov, Michele Ceriotti:
Optimal radial basis for density-based atomic representations. CoRR abs/2105.08717 (2021) - 2020
- [j6]Guillaume Fraux
Chemiscope: interactive structure-property explorer for materials and molecules. J. Open Source Softw. 5(51): 2117 (2020) - [j5]Benjamin A. Helfrecht
Structure-property maps with Kernel principal covariates regression. Mach. Learn. Sci. Technol. 1(4): 45021 (2020) - [i3]Benjamin A. Helfrecht, Rose K. Cersonsky, Guillaume Fraux, Michele Ceriotti:
Structure-Property Maps with Kernel Principal Covariates Regression. CoRR abs/2002.05076 (2020) - [i2]Giulio Imbalzano, Yongbin Zhuang, Venkat Kapil, Kevin Rossi, Edgar A. Engel, Federico Grasselli, Michele Ceriotti:
Uncertainty estimation by committee models for molecular dynamics and thermodynamic averages. CoRR abs/2011.08828 (2020) - [i1]Rose K. Cersonsky, Benjamin A. Helfrecht, Edgar A. Engel, Michele Ceriotti:
Improving Sample and Feature Selection with Principal Covariates Regression. CoRR abs/2012.12253 (2020)
2010 – 2019
- 2019
- [j4]Venkat Kapil, Mariana Rossi
i-PI 2.0: A universal force engine for advanced molecular simulations. Comput. Phys. Commun. 236: 214-223 (2019) - 2017
- [j3]Sandip De
Mapping and classifying molecules from a high-throughput structural database. J. Cheminformatics 9(1): 6:1-6:14 (2017) - 2016
- [j2]Riccardo Petraglia, Adrien Nicolaï, Matthew D. Wodrich
Beyond static structures: Putting forth REMD as a tool to solve problems in computational organic chemistry. J. Comput. Chem. 37(1): 83-92 (2016) - 2014
- [j1]Michele Ceriotti
i-PI: A Python interface for ab initio path integral molecular dynamics simulations. Comput. Phys. Commun. 185(3): 1019-1026 (2014) - 2010
- [c1]Michele Ceriotti
The delta-thermostat: selective normal-modes excitation by colored-noise Langevin dynamics. ICCS 2010: 1607-1614
Coauthor Index
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last updated on 2024-12-02 22:30 CET by the dblp team
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