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Benoit Da Mota

Showing results (1-10 of 7) with videos related to

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Journal of Cheminformatics|October 3, 2021
Scalable estimator of the diversity for de novo molecular generation resulting in a more robust QM dataset (OD9) and a more efficient molecular optimizationJules Leguy, Marta Glavatskikh, Thomas Cauchy, et al.
Journal of Cheminformatics|January 12, 2021
Dataset's chemical diversity limits the generalizability of machine learning predictionsMarta Glavatskikh, Jules Leguy, Gilles Hunault, et al.
Journal of Cheminformatics|January 12, 2021
EvoMol: a flexible and interpretable evolutionary algorithm for unbiased de novo molecular generationJules Leguy, Thomas Cauchy, Marta Glavatskikh, et al.
Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention|March 1, 2014
Enhancing the reproducibility of group analysis with randomized brain parcellationsBenoit Da Mota, Virgile Fritsch, Gaël Varoquaux, et al.
Frontiers in Neuroinformatics|May 1, 2014
Machine learning patterns for neuroimaging-genetic studies in the cloudBenoit Da Mota, Radu Tudoran, Alexandru Costan, et al.
Neuroimage|November 23, 2013
Randomized parcellation based inferenceBenoit Da Mota, Virgile Fritsch, Gaël Varoquaux, et al.
Neuroimage|March 4, 2015
Robust regression for large-scale neuroimaging studiesVirgile Fritsch, Benoit Da Mota, Eva Loth, et al.
Pageof 1

Showing results (1-10 of 7) with videos related to

Sort By:
Pageof 1
Journal of Cheminformatics|October 3, 2021
Scalable estimator of the diversity for de novo molecular generation resulting in a more robust QM dataset (OD9) and a more efficient molecular optimizationJules Leguy, Marta Glavatskikh, Thomas Cauchy, et al.
Journal of Cheminformatics|January 12, 2021
Dataset's chemical diversity limits the generalizability of machine learning predictionsMarta Glavatskikh, Jules Leguy, Gilles Hunault, et al.
Journal of Cheminformatics|January 12, 2021
EvoMol: a flexible and interpretable evolutionary algorithm for unbiased de novo molecular generationJules Leguy, Thomas Cauchy, Marta Glavatskikh, et al.
Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention|March 1, 2014
Enhancing the reproducibility of group analysis with randomized brain parcellationsBenoit Da Mota, Virgile Fritsch, Gaël Varoquaux, et al.
Frontiers in Neuroinformatics|May 1, 2014
Machine learning patterns for neuroimaging-genetic studies in the cloudBenoit Da Mota, Radu Tudoran, Alexandru Costan, et al.
Neuroimage|November 23, 2013
Randomized parcellation based inferenceBenoit Da Mota, Virgile Fritsch, Gaël Varoquaux, et al.
Neuroimage|March 4, 2015
Robust regression for large-scale neuroimaging studiesVirgile Fritsch, Benoit Da Mota, Eva Loth, et al.
Pageof 1