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Journal Articles
- 2021
[j3]Jules Leguy
, Marta Glavatskikh, Thomas Cauchy, Benoit Da Mota:
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)- 2020
- [j2]Jules Leguy, Thomas Cauchy, Marta Glavatskikh, Béatrice Duval, Benoit Da Mota:
EvoMol: a flexible and interpretable evolutionary algorithm for unbiased de novo molecular generation. J. Cheminformatics 12(1): 55 (2020) - 2019
- [j1]Marta Glavatskikh, Jules Leguy, Gilles Hunault, Thomas Cauchy, Benoit Da Mota:
Dataset's chemical diversity limits the generalizability of machine learning predictions. J. Cheminformatics 11(1): 69:1-69:15 (2019)
Conference and Workshop Papers
- 2021
- [c3]Jules Leguy, Béatrice Duval, Benoit Da Mota, Thomas Cauchy:
Surrogate-Based Black-Box Optimization Method for Costly Molecular Properties. ICTAI 2021: 780-785 - 2019
- [c2]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 - [c1]Jules Leguy, Thomas Cauchy, Béatrice Duval, Benoit Da Mota:
Predicting Interatomic Distances of Molecular Quantum Chemistry Calculations. EGC (best of volume) 2019: 159-174
Informal and Other Publications
- 2021
- [i1]Jules Leguy, Thomas Cauchy, Béatrice Duval, Benoit Da Mota:
Surrogate-Based Black-Box Optimization Method for Costly Molecular Properties. CoRR abs/2110.03522 (2021)
Coauthor Index
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