Filippo Bigi

11 papers A* 1Journal 10

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
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`	The dark side of the forces: assessing non-conservative force models for atomistic machine learning. CoRR Filippo Bigi, Marcel F. Langer, 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`	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