3 citations · 6 across the 3 of their papers we have counts for
3 papers
Generative Molecular Design with Steerable and Granular Synthesizability Control
Jeff Guo, Víctor Sabanza-Gil, Olha Semenenko +20
Designing molecules that are both property-optimal and readily synthesizable is a central challenge in drug discovery. Existing works that do consider synthesizability can jointly…
Best Practices for Multi-Fidelity Bayesian Optimization in Materials and Molecular Research
Víctor Sabanza-Gil, Riccardo Barbano, Daniel Pacheco Gutiérrez +4
Multi-fidelity Bayesian Optimization (MFBO) is a promising framework to speed up materials and molecular discovery as sources of information of different accuracies are at hand at…
Holistic chemical evaluation reveals pitfalls in reaction prediction models
Victor Sabanza Gil, Andres M. Bran, Malte Franke +3
The prediction of chemical reactions has gained significant interest within the machine learning community in recent years, owing to its complexity and crucial applications in chem…