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Echantillonnage à posteriori par méthode MCMC - réseau inversible
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This python module contains utilities to manipulate batches of DFT and DFTB calculations with a certain level of abstraction. It also contains a wide part dedicated to the prediction and manipulation of repulsion curves for DFTB Slater-Koster files.
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Implementation of the DIRECT algorithm for single criteria black box optimization.
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ulysse durand / caplab
GNU General Public License v3.0 or laterUpdated -
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An advanced AI for TFT, using state-of-the-art machine learning algorithms to make fast decisions in a competitive environment
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