3 papers
cs.LG2025
A study of EHVI vs fixed scalarization for molecule design
Anabel Yong, Austin Tripp, Layla Hosseini-Gerami +1
Multi-objective Bayesian optimization (MOBO) provides a principled framework for navigating trade-offs in molecular design. However, its empirical advantages over scalarized altern…
cs.LG2025
Hash Collisions in Molecular Fingerprints: Effects on Property Prediction and Bayesian Optimization
Walter Virany, Austin Tripp
Molecular fingerprinting methods use hash functions to create fixed-length vector representations of molecules. However, hash collisions cause distinct substructures to be represen…
cs.LG2025
Chemist-aligned retrosynthesis by ensembling diverse inductive bias models
Krzysztof Maziarz, Guoqing Liu, Hubert Misztela +8
Chemical synthesis remains a critical bottleneck in the discovery and manufacture of functional small molecules. AI-based synthesis planning models could be a potential remedy to f…