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Clémence Corminboeuf
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2020 – today
- 2024
- [j9]Frédéric Célerse
, Matthew D. Wodrich
From Organic Fragments to Photoswitchable Catalysts: The OFF-ON Structural Repository for Transferable Kernel-Based Potentials. J. Chem. Inf. Model. 64(4): 1201-1212 (2024) - [j8]Puck van Gerwen
3DReact: Geometric Deep Learning for Chemical Reactions. J. Chem. Inf. Model. 64(15): 5771-5785 (2024) - [i2]Matthieu Haeberle, Puck van Gerwen, Rubén Laplaza, Ksenia R. Briling, Jan Weinreich, Friedrich Eisenbrand, Clémence Corminboeuf:
Integer linear programming for unsupervised training set selection in molecular machine learning. CoRR abs/2410.16122 (2024) - 2023
- [j7]Puck van Gerwen
Reply to Comment on 'Physics-based representations for machine learning properties of chemical reactions'. Mach. Learn. Sci. Technol. 4(4): 48002 (2023) - [i1]Puck van Gerwen, Ksenia R. Briling, Charlotte Bunne, Vignesh Ram Somnath, Rubén Laplaza, Andreas Krause, Clémence Corminboeuf:
EquiReact: An equivariant neural network for chemical reactions. CoRR abs/2312.08307 (2023) - 2022
- [j6]Raimon Fabregat
Metric learning for kernel ridge regression: assessment of molecular similarity. Mach. Learn. Sci. Technol. 3(3): 35015 (2022) - [j5]Puck van Gerwen
Physics-based representations for machine learning properties of chemical reactions. Mach. Learn. Sci. Technol. 3(4): 45005 (2022)
2010 – 2019
- 2016
- [j4]Riccardo Petraglia, Adrien Nicolaï, Matthew D. Wodrich
Beyond static structures: Putting forth REMD as a tool to solve problems in computational organic chemistry. J. Comput. Chem. 37(1): 83-92 (2016) - 2013
- [j3]Laetitia Bomble, Stephan N. Steinmann
Bonding analysis of planar hypercoordinate atoms via the generalized BLW-LOL. J. Comput. Chem. 34(26): 2242-2248 (2013) - 2012
- [j2]Fabrice Avaltroni, Clémence Corminboeuf:
Identifying clusters as low-lying mimina - efficiency of stochastic and genetic algorithms using inexpensive electronic structure levels. J. Comput. Chem. 33(5): 502-508 (2012) - 2011
- [j1]Fabrice Avaltroni, Clémence Corminboeuf:
Efficiency of random search procedures along the silicon cluster series: Sin (n = 5-10, 15, and 20). J. Comput. Chem. 32(9): 1869-1875 (2011)
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