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Molecular dynamics simulations using the drude polarizable force field on GPUs with OpenMM: Implementation, validation, and benchmarks., , , и . J. Comput. Chem., 39 (21): 1682-1689 (2018)Fast Flexible Modeling of RNA Structure Using Internal Coordinates., , , , и . IEEE ACM Trans. Comput. Biol. Bioinform., 8 (5): 1247-1257 (2011)Weakly-Supervised Deep Learning of Heat Transport via Physics Informed Loss., , , , и . CoRR, (2018)OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials., , , , , , , , , и 12 other автор(ы). CoRR, (2023)Solving the RNA design problem with reinforcement learning., , , и . PLoS Comput. Biol., (2018)OpenMM 7: Rapid development of high performance algorithms for molecular dynamics., , , , , , , , , и 3 other автор(ы). PLoS Comput. Biol., (2017)NNP/MM: Accelerating Molecular Dynamics Simulations with Machine Learning Potentials and Molecular Mechanics., , , , , , , и . J. Chem. Inf. Model., 63 (18): 5701-5708 (сентября 2023)Efficient nonbonded interactions for molecular dynamics on a graphics processing unit., и . J. Comput. Chem., 31 (6): 1268-1272 (2010)TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations., , , , , , , , и . CoRR, (2024)Accelerating molecular dynamic simulation on graphics processing units., , , , , , , , и . J. Comput. Chem., 30 (6): 864-872 (2009)