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Federico Errica

Showing results (1-10 of 6) with videos related to

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The Journal of Chemical Physics|December 18, 2023
Self-tuning Hamiltonian Monte Carlo for accelerated samplingHenrik Christiansen, Federico Errica, Francesco Alesiani
Frontiers in Artificial Intelligence|February 21, 2022
Catastrophic Forgetting in Deep Graph Networks: A Graph Classification BenchmarkAntonio Carta, Andrea Cossu, Federico Errica, et al.
Neural Networks : the Official Journal of the International Neural Network Society|June 20, 2020
A gentle introduction to deep learning for graphsDavide Bacciu, Federico Errica, Alessio Micheli, et al.
Plos One|May 20, 2025
Assessing the generalization capabilities of TCR binding predictors via peptide distance analysisLeonardo V Castorina, Filippo Grazioli, Pierre Machart, et al.
The Journal of Chemical Physics|November 11, 2025
Fast, modular, and differentiable framework for machine learning-enhanced molecular simulationsHenrik Christiansen, Takashi Maruyama, Federico Errica, et al.
Frontiers in Molecular Biosciences|May 17, 2021
A Deep Graph Network-Enhanced Sampling Approach to Efficiently Explore the Space of Reduced Representations of ProteinsFederico Errica, Marco Giulini, Davide Bacciu, et al.
Pageof 1

Showing results (1-10 of 6) with videos related to

Sort By:
Pageof 1
The Journal of Chemical Physics|December 18, 2023
Self-tuning Hamiltonian Monte Carlo for accelerated samplingHenrik Christiansen, Federico Errica, Francesco Alesiani
Frontiers in Artificial Intelligence|February 21, 2022
Catastrophic Forgetting in Deep Graph Networks: A Graph Classification BenchmarkAntonio Carta, Andrea Cossu, Federico Errica, et al.
Neural Networks : the Official Journal of the International Neural Network Society|June 20, 2020
A gentle introduction to deep learning for graphsDavide Bacciu, Federico Errica, Alessio Micheli, et al.
Plos One|May 20, 2025
Assessing the generalization capabilities of TCR binding predictors via peptide distance analysisLeonardo V Castorina, Filippo Grazioli, Pierre Machart, et al.
The Journal of Chemical Physics|November 11, 2025
Fast, modular, and differentiable framework for machine learning-enhanced molecular simulationsHenrik Christiansen, Takashi Maruyama, Federico Errica, et al.
Frontiers in Molecular Biosciences|May 17, 2021
A Deep Graph Network-Enhanced Sampling Approach to Efficiently Explore the Space of Reduced Representations of ProteinsFederico Errica, Marco Giulini, Davide Bacciu, et al.
Pageof 1