Michele Ceriotti

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 26

Top Topics

Cartesian Coordinates

Trained Neural Networks

Feature Selection

Top Venues

Mach. Learn. Sci. Technol.

Comput. Phys. Commun.

J. Comput. Chem.

Publications

Marcel F. Langer, Sergey N. Pozdnyakov, Michele Ceriotti
Probing the effects of broken symmetries in machine learning. CoRR (2024)
Filippo Bigi, Sanggyu Chong, Michele Ceriotti, Federico Grasselli
A prediction rigidity formalism for low-cost uncertainties in trained neural networks. CoRR (2024)
Matthias Kellner, Michele Ceriotti
Uncertainty quantification by direct propagation of shallow ensembles. Mach. Learn. Sci. Technol. 5 (3) (2024)
Kevin K. Huguenin-Dumittan, Philip Loche, Haoran Ni, Michele Ceriotti
Physics-inspired Equivariant Descriptors of Non-bonded Interactions. CoRR (2023)
Sergey Pozdnyakov, Michele Ceriotti
Smooth, exact rotational symmetrization for deep learning on point clouds. NeurIPS (2023)
Filippo Bigi, Michele Ceriotti
Fast evaluation of real spherical harmonics and their derivatives in Cartesian coordinates. CoRR (2023)
Edoardo Cignoni, Divya Suman, Jigyasa Nigam, Lorenzo Cupellini, Benedetta Mennucci, Michele Ceriotti
Electronic excited states from physically-constrained machine learning. CoRR (2023)
Jigyasa Nigam, Sergey N. Pozdnyakov, Kevin K. Huguenin-Dumittan, Michele Ceriotti
Completeness of Atomic Structure Representations. CoRR (2023)
Filippo Bigi, Sergey N. Pozdnyakov, Michele Ceriotti
Wigner kernels: body-ordered equivariant machine learning without a basis. CoRR (2023)
Sergey N. Pozdnyakov, Michele Ceriotti
Smooth, exact rotational symmetrization for deep learning on point clouds. CoRR (2023)
Chiheb Ben Mahmoud, Federico Grasselli, Michele Ceriotti
Predicting hot electrons free energies from ground-state data. CoRR (2022)
Sergey N. Pozdnyakov, Michele Ceriotti
Incompleteness of graph neural networks for points clouds in three dimensions. Mach. Learn. Sci. Technol. 3 (4) (2022)
Filippo Bigi, Kevin Huguenin-Dumittan, Michele Ceriotti, David E. Manolopoulos
A smooth basis for atomistic machine learning. CoRR (2022)
Jigyasa Nigam, Guillaume Fraux, Michele Ceriotti
Unified theory of atom-centered representations and graph convolutional machine-learning schemes. CoRR (2022)
Sergey N. Pozdnyakov, Michele Ceriotti
Incompleteness of graph convolutional neural networks for points clouds in three dimensions. CoRR (2022)
Rose K. Cersonsky, Benjamin A. Helfrecht, Edgar A. Engel, Sergei Kliavinek, Michele Ceriotti
Improving sample and feature selection with principal covariates regression. Mach. Learn. Sci. Technol. 2 (3) (2021)
Alexander Goscinski, Felix Musil, Sergey Pozdnyakov, Michele Ceriotti
Optimal radial basis for density-based atomic representations. CoRR (2021)
Alexander Goscinski, Guillaume Fraux, Giulio Imbalzano, Michele Ceriotti
The role of feature space in atomistic learning. Mach. Learn. Sci. Technol. 2 (2) (2021)
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 (2020)
Benjamin A. Helfrecht, Rose K. Cersonsky, Guillaume Fraux, Michele Ceriotti
Structure-Property Maps with Kernel Principal Covariates Regression. CoRR (2020)
Guillaume Fraux, Rose K. Cersonsky, Michele Ceriotti
Chemiscope: interactive structure-property explorer for materials and molecules. J. Open Source Softw. 5 (51) (2020)
Benjamin A. Helfrecht, Rose K. Cersonsky, Guillaume Fraux, Michele Ceriotti
Structure-property maps with Kernel principal covariates regression. Mach. Learn. Sci. Technol. 1 (4) (2020)
Rose K. Cersonsky, Benjamin A. Helfrecht, Edgar A. Engel, Michele Ceriotti
Improving Sample and Feature Selection with Principal Covariates Regression. CoRR (2020)
Venkat Kapil, Mariana Rossi, Ondrej Marsalek, Riccardo Petraglia, Yair Litman, Thomas Spura, Bingqing Cheng, Alice Cuzzocrea, Robert H. Meißner, David M. Wilkins, Benjamin A. Helfrecht, Przemyslaw Juda, Sébastien P. Bienvenue, Wei Fang, Jan Kessler, Igor Poltavsky, Steven Vandenbrande, Jelle Wieme, Michele Ceriotti
i-PI 2.0: A universal force engine for advanced molecular simulations. Comput. Phys. Commun. 236 (2019)
Sandip De, Felix Musil, Teresa Ingram, Carsten Baldauf, Michele Ceriotti
Mapping and classifying molecules from a high-throughput structural database. J. Cheminformatics 9 (1) (2017)
Riccardo Petraglia, Adrien Nicolaï, Matthew D. Wodrich, Michele Ceriotti, Clemence Corminboeuf
Beyond static structures: Putting forth REMD as a tool to solve problems in computational organic chemistry. J. Comput. Chem. 37 (1) (2016)
Michele Ceriotti, Joshua More, David E. Manolopoulos
i-PI: A Python interface for ab initio path integral molecular dynamics simulations. Comput. Phys. Commun. 185 (3) (2014)
Michele Ceriotti, Michele Parrinello
The delta-thermostat: selective normal-modes excitation by colored-noise Langevin dynamics. ICCS (1) (2010)