Michele Ceriotti

39 papers A* 2Misc 1Journal 36

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	How unconstrained machine-learning models learn physical symmetries. CoRR Michelangelo Domina, Joseph William Abbott, Paolo Pegolo, Filippo Bigi, Michele Ceriotti
2026	J	`jnl`	Learning Long-Range Representations with Equivariant Messages. Trans. Mach. Learn. Res. Egor Rumiantsev, Marcel F. Langer, Tulga-Erdene Sodjargal, Michele Ceriotti, Philip Loche
2025	J	`jnl`	Comparing the latent features of universal machine-learning interatomic potentials. CoRR Sofiia Chorna, Davide Tisi, Cesare Malosso, Wei Bin How, Michele Ceriotti, Sanggyu Chong
2025	J	`jnl`	FlashMD: long-stride, universal prediction of molecular dynamics. CoRR Filippo Bigi, Sanggyu Chong, Agustinus Kristiadi, Michele Ceriotti
2025	J	`jnl`	PET-MAD, a universal interatomic potential for advanced materials modeling. CoRR Arslan Mazitov, Filippo Bigi, Matthias Kellner, Paolo Pegolo, Davide Tisi, Guillaume Fraux, Sergey Pozdnyakov, Philip Loche, Michele Ceriotti
2025	J	`jnl`	Representing spherical tensors with scalar-based machine-learning models. CoRR Michelangelo Domina, Filippo Bigi, Paolo Pegolo, Michele Ceriotti
2025	A*	`conf`	The dark side of the forces: assessing non-conservative force models for atomistic machine learning. ICML Filippo Bigi, Marcel F. Langer, Michele Ceriotti
2024	J	`jnl`	A prediction rigidity formalism for low-cost uncertainties in trained neural networks. CoRR Filippo Bigi, Sanggyu Chong, Michele Ceriotti, Federico Grasselli
2024	J	`jnl`	A prediction rigidity formalism for low-cost uncertainties in trained neural networks. Mach. Learn. Sci. Technol. Filippo Bigi, Sanggyu Chong, Michele Ceriotti, Federico Grasselli
2024	J	`jnl`	Could ChatGPT get an Engineering Degree? Evaluating Higher Education Vulnerability to AI Assistants. CoRR 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, Giovanni Piccioli, Hadrien Sevel, Louis Coulon, Manuela Pineros-Rodriguez, Marin Bonnassies, Pierre Hellich, Puck van Gerwen, Sankalp Gambhir, Solal Pirelli, Thomas Blanchard, Timothée Callens, Toni Abi Aoun, Yannick Calvino Alonso, Yuri Cho, Alberto Silvio Chiappa, Antonio Sclocchi, Étienne Bruno, Florian Hofhammer, Gabriel Pescia, Geovani Rizk, Leello Dadi, Lucas Stoffl, Manoel Horta Ribeiro, Matthieu Bovel, Yueyang Pan, Aleksandra Radenovic, Alexandre Alahi, Alexander Mathis, Anne-Florence Bitbol, Boi Faltings, Cécile Hébert, Devis Tuia, François Maréchal, George Candea, Giuseppe Carleo, Jean-Cédric Chappelier, Nicolas Flammarion, Jean-Marie Fürbringer, Jean-Philippe Pellet, Karl Aberer, Lenka Zdeborová, Marcel Salathé, Martin Jaggi, Martin Rajman, Mathias Payer, Matthieu Wyart, Michael Gastpar, Michele Ceriotti, Ola Svensson, Olivier Lévêque, Paolo Ienne, Rachid Guerraoui, Robert West, Sanidhya Kashyap, Valerio Piazza, Viesturs Simanis, Viktor Kuncak, Volkan Cevher, Philippe Schwaller, Sacha Friedli, Patrick Jermann, Tanja Käser, Antoine Bosselut
2024	J	`jnl`	Probing the effects of broken symmetries in machine learning. CoRR Marcel F. Langer, Sergey N. Pozdnyakov, Michele Ceriotti
2024	J	`jnl`	Probing the effects of broken symmetries in machine learning. Mach. Learn. Sci. Technol. Marcel F. Langer, Sergey N. Pozdnyakov, Michele Ceriotti
2024	J	`jnl`	The dark side of the forces: assessing non-conservative force models for atomistic machine learning. CoRR Filippo Bigi, Marcel F. Langer, Michele Ceriotti
2024	J	`jnl`	Uncertainty quantification by direct propagation of shallow ensembles. Mach. Learn. Sci. Technol. Matthias Kellner, Michele Ceriotti
2023	J	`jnl`	Completeness of Atomic Structure Representations. CoRR Jigyasa Nigam, Sergey N. Pozdnyakov, Kevin K. Huguenin-Dumittan, Michele Ceriotti
2023	J	`jnl`	Electronic excited states from physically-constrained machine learning. CoRR Edoardo Cignoni, Divya Suman, Jigyasa Nigam, Lorenzo Cupellini, Benedetta Mennucci, Michele Ceriotti
2023	J	`jnl`	Fast evaluation of real spherical harmonics and their derivatives in Cartesian coordinates. CoRR Filippo Bigi, Michele Ceriotti
2023	J	`jnl`	Physics-inspired Equivariant Descriptors of Non-bonded Interactions. CoRR Kevin K. Huguenin-Dumittan, Philip Loche, Haoran Ni, Michele Ceriotti
2023	A*	`conf`	Smooth, exact rotational symmetrization for deep learning on point clouds. NeurIPS Sergey Pozdnyakov, Michele Ceriotti
2023	J	`jnl`	Smooth, exact rotational symmetrization for deep learning on point clouds. CoRR Sergey N. Pozdnyakov, Michele Ceriotti
2023	J	`jnl`	Wigner kernels: body-ordered equivariant machine learning without a basis. CoRR Filippo Bigi, Sergey N. Pozdnyakov, Michele Ceriotti
2022	J	`jnl`	A smooth basis for atomistic machine learning. CoRR Filippo Bigi, Kevin Huguenin-Dumittan, Michele Ceriotti, David E. Manolopoulos
2022	J	`jnl`	Incompleteness of graph convolutional neural networks for points clouds in three dimensions. CoRR Sergey N. Pozdnyakov, Michele Ceriotti
2022	J	`jnl`	Incompleteness of graph neural networks for points clouds in three dimensions. Mach. Learn. Sci. Technol. Sergey N. Pozdnyakov, Michele Ceriotti
2022	J	`jnl`	Predicting hot electrons free energies from ground-state data. CoRR Chiheb Ben Mahmoud, Federico Grasselli, Michele Ceriotti
2022	J	`jnl`	Unified theory of atom-centered representations and graph convolutional machine-learning schemes. CoRR Jigyasa Nigam, Guillaume Fraux, Michele Ceriotti
2021	J	`jnl`	Improving sample and feature selection with principal covariates regression. Mach. Learn. Sci. Technol. Rose K. Cersonsky, Benjamin A. Helfrecht, Edgar A. Engel, Sergei Kliavinek, Michele Ceriotti
2021	J	`jnl`	Optimal radial basis for density-based atomic representations. CoRR Alexander Goscinski, Felix Musil, Sergey Pozdnyakov, Michele Ceriotti
2021	J	`jnl`	The role of feature space in atomistic learning. Mach. Learn. Sci. Technol. Alexander Goscinski, Guillaume Fraux, Giulio Imbalzano, Michele Ceriotti
2020	J	`jnl`	Chemiscope: interactive structure-property explorer for materials and molecules. J. Open Source Softw. Guillaume Fraux, Rose K. Cersonsky, Michele Ceriotti
2020	J	`jnl`	Improving Sample and Feature Selection with Principal Covariates Regression. CoRR Rose K. Cersonsky, Benjamin A. Helfrecht, Edgar A. Engel, Michele Ceriotti
2020	J	`jnl`	Structure-Property Maps with Kernel Principal Covariates Regression. CoRR Benjamin A. Helfrecht, Rose K. Cersonsky, Guillaume Fraux, Michele Ceriotti
2020	J	`jnl`	Structure-property maps with Kernel principal covariates regression. Mach. Learn. Sci. Technol. Benjamin A. Helfrecht, Rose K. Cersonsky, Guillaume Fraux, Michele Ceriotti
2020	J	`jnl`	Uncertainty estimation by committee models for molecular dynamics and thermodynamic averages. CoRR Giulio Imbalzano, Yongbin Zhuang, Venkat Kapil, Kevin Rossi, Edgar A. Engel, Federico Grasselli, Michele Ceriotti
2019	J	`jnl`	i-PI 2.0: A universal force engine for advanced molecular simulations. Comput. Phys. Commun. 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
2017	J	`jnl`	Mapping and classifying molecules from a high-throughput structural database. J. Cheminformatics Sandip De, Felix Musil, Teresa Ingram, Carsten Baldauf, Michele Ceriotti
2016	J	`jnl`	Beyond static structures: Putting forth REMD as a tool to solve problems in computational organic chemistry. J. Comput. Chem. Riccardo Petraglia, Adrien Nicolaï, Matthew D. Wodrich, Michele Ceriotti, Clémence Corminboeuf
2014	J	`jnl`	i-PI: A Python interface for ab initio path integral molecular dynamics simulations. Comput. Phys. Commun. Michele Ceriotti, Joshua More, David E. Manolopoulos
2010	Misc	`conf`	The delta-thermostat: selective normal-modes excitation by colored-noise Langevin dynamics. ICCS Michele Ceriotti, Michele Parrinello