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The authors gratefully acknowledge the Gauss Centre for Supercomputing e.V. (www.gauss-centre.eu) for funding this project by providing computing time through the John von Neumann Institute for Computing (NIC) on the GCS Supercomputer JUWELS at Jülich Supercomputing Centre (JSC). The project received funding from the Helmholtz European Partnering program (``Innovative high-performance computing approaches for molecular neuromedicine").
Input files, molecular dynamics and OPES trajectories, CGenFF and DFTB3/3ob potential energies, and normalizing flow neural network models generated for the journal article: "Multimap targeted free energy estimation." Rizzi, Andrea, Paolo Carloni, and Michele Parrinello. arXiv preprint arXiv:2302.07683 (2023).
Chemical Physics (physics.chem-ph), quantum mechanics, FOS: Physical sciences, Computational Physics (physics.comp-ph), machine learning, normalizing flows, drug binding, Physics - Chemical Physics, free energy perturbation, molecular simulations, Physics - Computational Physics
Chemical Physics (physics.chem-ph), quantum mechanics, FOS: Physical sciences, Computational Physics (physics.comp-ph), machine learning, normalizing flows, drug binding, Physics - Chemical Physics, free energy perturbation, molecular simulations, Physics - Computational Physics
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