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Benoit Da Mota
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2020 – today
- 2021
- [j8]Jules Leguy
, Marta Glavatskikh
Scalable estimator of the diversity for de novo molecular generation resulting in a more robust QM dataset (OD9) and a more efficient molecular optimization. J. Cheminformatics 13(1): 76 (2021) - [c7]Jules Leguy, Béatrice Duval, Benoit Da Mota, Thomas Cauchy
Surrogate-Based Black-Box Optimization Method for Costly Molecular Properties. ICTAI 2021: 780-785 - [i2]Jules Leguy, Thomas Cauchy, Béatrice Duval, Benoit Da Mota:
Surrogate-Based Black-Box Optimization Method for Costly Molecular Properties. CoRR abs/2110.03522 (2021) - 2020
- [j7]Jules Leguy
EvoMol: a flexible and interpretable evolutionary algorithm for unbiased de novo molecular generation. J. Cheminformatics 12(1): 55 (2020)
2010 – 2019
- 2019
- [j6]Marta Glavatskikh
Dataset's chemical diversity limits the generalizability of machine learning predictions. J. Cheminformatics 11(1): 69:1-69:15 (2019) - [c6]Jules Leguy, Thomas Cauchy, Béatrice Duval, Benoit Da Mota:
Des réseaux de neurones pour prédire des distances interatomiques extraites d'une base de données ouverte de calculs en chimie quantique. EGC 2019: 9-20 - [c5]Jules Leguy, Thomas Cauchy
Predicting Interatomic Distances of Molecular Quantum Chemistry Calculations. EGC (best of volume) 2019: 159-174 - 2015
- [j5]Virgile Fritsch, Benoit Da Mota, Eva Loth
Robust regression for large-scale neuroimaging studies. NeuroImage 111: 431-441 (2015) - 2014
- [j4]Benoit Da Mota, Radu Tudoran, Alexandru Costan
Generic Machine Learning Pattern for Neuroimaging-Genetic Studies in the Cloud. Frontiers Neuroinformatics 8: 31 (2014) - [j3]Benoit Da Mota, Virgile Fritsch, Gaël Varoquaux
Randomized parcellation based inference. NeuroImage 89: 203-215 (2014) - 2013
- [c4]Benoit Da Mota, Virgile Fritsch, Gaël Varoquaux
Enhancing the Reproducibility of Group Analysis with Randomized Brain Parcellations. MICCAI (2) 2013: 591-598 - [c3]Virgile Fritsch, Benoit Da Mota, Gaël Varoquaux
Robust Group-Level Inference in Neuroimaging Genetic Studies. PRNI 2013: 21-24 - 2012
- [i1]Gabriel Antoniu, Alexandru Costan, Benoit Da Mota, Bertrand Thirion, Radu Tudoran:
A-Brain: Using the Cloud to Understand the Impact of Genetic Variability on the Brain. ERCIM News 2012(89) (2012) - 2011
- [j2]Benoit Da Mota:
Équivalences et forme prénexe pour les formules booléennes quantifiées. Rev. d'Intelligence Artif. 25(6): 717-742 (2011) - 2010
- [b1]Benoit Da Mota:
Formules booléennes quantifiées : transformations formelles et calculs parallèles. (Quantified boolean formulae : formal processings and parallel computations). University of Angers, France, 2010 - [c2]Benoit Da Mota, Pascal Nicolas, Igor Stéphan:
A new parallel architecture for QBF tools. HPCS 2010: 324-330
2000 – 2009
- 2009
- [j1]Igor Stéphan, Benoit Da Mota, Pascal Nicolas:
From (Quantified) Boolean Formulae to Answer Set Programming. J. Log. Comput. 19(4): 565-590 (2009) - [c1]Igor Stéphan, Benoit Da Mota:
A Unified Framework for Certificate and Compilation for QBF. ICLA 2009: 210-223
Coauthor Index
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