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Continual Prune-and-Select: Class-incremental learning with specialized subnetworks., , , и . CoRR, (2022)Continual prune-and-select: class-incremental learning with specialized subnetworks., , , и . Appl. Intell., 53 (14): 17849-17864 (июля 2023)First-principles study of solute-dislocation interaction in aluminum-rich alloys, , и . Phys. Rev. B, 64 (22): 224203 (ноября 2001)Impurity diffusion activation energies in Al from first principles, и . Phys. Rev. B, 79 (5): 054304 (февраля 2009)Neural network relief: a pruning algorithm based on neural activity., , , и . CoRR, (2021)Ab Initio Study of Hydrogen Hydrate Clathrates for Hydrogen Storage within the ITBL Environment., , , , , , , и . ISHPC, том 2858 из Lecture Notes in Computer Science, стр. 330-341. Springer, (2003)Realization of a Computer Simulation Environment Based on ITBL and a Large Scale GW Calculation Performed on This Platform., , , , , , , , и . ISHPC, том 4759 из Lecture Notes in Computer Science, стр. 427-433. Springer, (2005)Neural network relief: a pruning algorithm based on neural activity., , , и . Mach. Learn., 113 (5): 2597-2618 (мая 2024)MEAMfit: A reference-free modified embedded atom method (RF-MEAM) energy and force-fitting code., , , , и . Comput. Phys. Commun., (2015)Brute Force Composition Scanning with a CALPHAD Database to Find Low Temperature Body Centered Cubic High Entropy Alloys., , и . Entropy, 20 (12): 911 (2018)