Real-time feedback from iterative electronic structure calculations. - Alain C. Vaucher; Moritz P. Haag; Markus Reiher (J. Comput. Chem., 2016)

Molecular Propensity as a Driver for Explorative Reactivity Studies. - Alain C. Vaucher; Markus Reiher (J. Chem. Inf. Model., 2016)

Training neural nets to learn reactive potential energy surfaces using interactive quantum chemistry in virtual reality. - Silvia Amabilino; Lars A. Bratholm; Simon J. Bennie; Alain C. Vaucher; Markus Reiher; David R. Glowacki (CoRR, 2019)

GuacaMol: Benchmarking Models for de Novo Molecular Design. - Nathan Brown; Marco Fiscato; Marwin H. S. Segler; Alain C. Vaucher (J. Chem. Inf. Model., 2019)

Neural Machine Translation for Conditional Generation of Novel Procedures. - Joppe Geluykens; Sandra Mitrovic; Carlos Ortega Vázquez; Teodoro Laino; Alain C. Vaucher; Jochen De Weerdt (HICSS, 2021)

Prediction of chemical reaction yields using deep learning. - Philippe Schwaller; Alain C. Vaucher; Teodoro Laino; Jean-Louis Reymond (Mach. Learn. Sci. Technol., 2021)

Mapping the space of chemical reactions using attention-based neural networks. - Philippe Schwaller; Daniel Probst; Alain C. Vaucher; Vishnu H. Nair; David Kreutter; Teodoro Laino; Jean-Louis Reymond (Nat. Mach. Intell., 2021)

Standardizing chemical compounds with language models. - Miruna T. Cretu; Alessandra Toniato; Amol Thakkar; Amin A Debabeche; Teodoro Laino; Alain C. Vaucher (Mach. Learn. Sci. Technol., 2023)