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Pietro Novelli

  1. Learning Dynamical Systems via Koopman Operator Regression in Reproducing Kernel Hilbert Spaces
    2022/05/27 by Vladimir R. Kostic, Pietro Novelli, Kostic, Vladimir +9 · 14 citations
    Computer Science · Engineering · Physics and Astronomy · #Dynamical Systems (math.DS) #FOS: Computer and information sciences #FOS: Mathematics #Fluid Dynamics and Turbulent Flows #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Model Reduction and Neural Networks
  2. Sharp Spectral Rates for Koopman Operator Learning
    2023/02/03 by Vladimir R. Kostic, Kostic, Vladimir, Karim Lounici +5 · 8 citations
    Physics and Astronomy · Medicine · Computer Science · #Model Reduction and Neural Networks #Thermal Regulation in Medicine #Gaussian Processes and Bayesian Inference
  3. Neural Conditional Probability for Uncertainty Quantification
    2024/07/01 by Vladimir Kostić, Karim Lounici, Kostic, Vladimir R. +9 · 6 citations
    Computer Science · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #Neural Networks and Applications #Statistics Theory (math.ST)
  4. Estimating Koopman operators with sketching to provably learn large scale dynamical systems
    2023/06/07 by Giacomo Meanti, Meanti, Giacomo, Antoine Chatalic +9 · 3 citations
    Computer Science · Physics and Astronomy · #Dynamical Systems (math.DS) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and ELM #Model Reduction and Neural Networks #Neural Networks and Applications
  5. Transfer learning for atomistic simulations using GNNs and kernel mean embeddings
    2023/06/02 by Isak Falk, Falk, John, Pietro Novelli +5 · 2 citations
    Computer Science · Materials Science · #Advanced Graph Neural Networks #Chemical Physics (physics.chem-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning in Materials Science #Topic Modeling
  6. Laplace Transform Based Low-Complexity Learning of Continuous Markov Semigroups
    2024/10/18 by Vladimir Kostić, Karim Lounici, Kostic, Vladimir R. +9 · 2 citations
    Computer Science · Engineering · #Control Systems and Identification #FOS: Computer and information sciences #FOS: Mathematics #Fault Detection and Control Systems #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Statistics Theory (math.ST)
  7. Dynamics Harmonic Analysis of Robotic Systems: Application in Data-Driven Koopman Modelling
    2023/12/12 by Daniel Ordoñez-Apraez, Vladimir Kostić, Ordoñez-Apraez, Daniel +11 · 1 citation
    Physics and Astronomy · #Model Reduction and Neural Networks
  8. Fast and Fourier Features for Transfer Learning of Interatomic Potentials
    2025/05/08 by Pietro Novelli, Novelli, Pietro, Giacomo Meanti +10 · 3 citations
    Materials Science · Physics and Astronomy · #Advanced Chemical Physics Studies #Computational Physics (physics.comp-ph) #FOS: Physical sciences #Machine Learning in Materials Science #Quantum many-body systems