Scalable estimator of the diversity for de novo molecular generation resulting in a more robust QM dataset (OD9) and a more efficient molecular optimization von Leguy, Jules, Glavatskikh, Marta, Cauchy, Thomas, Da Mota, Benoit

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EvoMol: a flexible and interpretable evolutionary algorithm for unbiased de novo molecular generation von Leguy, Jules, Cauchy, Thomas, Glavatskikh, Marta, Duval, Béatrice, Da Mota, Benoit

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Dataset’s chemical diversity limits the generalizability of machine learning predictions von Glavatskikh, Marta, Leguy, Jules, Hunault, Gilles, Cauchy, Thomas, Da Mota, Benoit

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Definition and exploration of realistic chemical spaces using the connectivity and cyclic features of ChEMBL and ZINC von Cauchy, Thomas, Leguy, Jules, Da Mota, Benoit

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From (Quantified) Boolean Formulae to Answer Set Programming von Stéphan, Igor, Da Mota, Benoit, Nicolas, Pascal

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Advances in Knowledge Discovery and Management: Volume 9 von Jaziri, Rakia, Martin, Arnaud, Rousset, Marie-Christine, Boudjeloud-Assala, Lydia, Guillet, Fabrice

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Robust regression for large-scale neuroimaging studies von Fritsch, Virgile, Da Mota, Benoit, Loth, Eva, Varoquaux, Gaël, Banaschewski, Tobias, Barker, Gareth J., Bokde, Arun L.W., Brühl, Rüdiger, Butzek, Brigitte, Conrod, Patricia, Flor, Herta, Garavan, Hugh, Lemaitre, Hervé, Mann, Karl, Nees, Frauke, Paus, Tomas, Schad, Daniel J., Schümann, Gunter, Frouin, Vincent, Poline, Jean-Baptiste, Thirion, Bertrand

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Randomized parcellation based inference von Da Mota, Benoit, Fritsch, Virgile, Varoquaux, Gaël, Banaschewski, Tobias, Barker, Gareth J., Bokde, Arun L.W., Bromberg, Uli, Conrod, Patricia, Gallinat, Jürgen, Garavan, Hugh, Martinot, Jean-Luc, Nees, Frauke, Paus, Tomas, Pausova, Zdenka, Rietschel, Marcella, Smolka, Michael N., Ströhle, Andreas, Frouin, Vincent, Poline, Jean-Baptiste, Thirion, Bertrand

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Machine learning patterns for neuroimaging-genetic studies in the cloud von Da Mota, Benoit, Tudoran, Radu, Costan, Alexandru, Varoquaux, Gaël, Brasche, Goetz, Conrod, Patricia, Lemaitre, Herve, Paus, Tomas, Rietschel, Marcella, Frouin, Vincent, Poline, Jean-Baptiste, Antoniu, Gabriel, Thirion, Bertrand

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Surrogate-Based Black-Box Optimization Method for Costly Molecular Properties von Leguy, Jules, Cauchy, Thomas, Duval, Beatrice, Da Mota, Benoit

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Generic Machine Learning Pattern for Neuroimaging-Genetic Studies in the Cloud von Da Mota, Benoit, Tudoran, Radu, Costan, Alexandru, Varoquaux, Gaël, Brasche, Goetz, Conrod, Patricia, Lemaitre, Hervé, Paus, Tomas, Rietschel, Marcella, Frouin, Vincent, Poline, Jean-Baptiste, Antoniu, Gabriel, Thirion, Bertrand

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OD9 dataset part 01/28 von Cauchy, Thomas, Mota, Benoit Da

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OD9 dataset part 02/28 von Cauchy, Thomas, Mota, Benoit Da

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Predicting Interatomic Distances of Molecular Quantum Chemistry Calculations von Leguy, Jules, Cauchy, Thomas, Duval, Béatrice, Da Mota, Benoit

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Additional file 2 of Scalable estimator of the diversity for de novo molecular generation resulting in a more robust QM dataset (OD9) and a more efficient molecular optimization von Leguy, Jules, Glavatskikh, Marta, Cauchy, Thomas, Da Mota, Benoit

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Surrogate-Based Black-Box Optimization Method for Costly Molecular Properties von Leguy, Jules, Cauchy, Thomas, Duval, Beatrice, Benoit Da Mota

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Enhancing the Reproducibility of Group Analysis with Randomized Brain Parcellations von Da Mota, Benoit, Fritsch, Virgile, Varoquaux, Gaël, Frouin, Vincent, Poline, Jean-Baptiste, Thirion, Bertrand

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PC9_data.zip von Cauchy, Thomas, Mota, Benoit Da, Glavastkikh, Marta

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A Unified Framework for Certificate and Compilation for QBF von Stéphan, Igor, Da Mota, Benoit

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Additional file 1 of EvoMol: a flexible and interpretable evolutionary algorithm for unbiased de novo molecular generation von Leguy, Jules, Cauchy, Thomas, Glavatskikh, Marta, Duval, Béatrice, Mota, Benoit Da

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