From the 1 of 3 linked papers with an AI index.
3 papers
PIKS: Universal Physics-Informed Kernel Methods
Joachim Bona-Pellissier, Giacomo Meanti, Matteo Santacesaria +1
The paper proposes Physics-Informed Kernel Methods (PIKS), a kernel-based approach that incorporates linear differential constraints into learning, proving universal consistency an…
kooplearn: A Scikit-Learn Compatible Library of Algorithms for Evolution Operator Learning
Giacomo Turri, Grégoire Pacreau, Giacomo Meanti +8
kooplearn is a machine-learning library that implements linear, kernel, and deep-learning estimators of dynamical operators and their spectral decompositions. kooplearn can model b…
Fast and Fourier Features for Transfer Learning of Interatomic Potentials
Pietro Novelli, Giacomo Meanti, Pedro J. Buigues +4
Training machine learning interatomic potentials that are both computationally and data-efficient is a key challenge for enabling their routine use in atomistic simulations. To thi…