3 papers
cs.LG2025
A Dataset for Distilling Knowledge Priors from Literature for Therapeutic Design
Haydn Thomas Jones, Natalie Maus, Josh Magnus Ludan +9
AI-driven discovery can greatly reduce design time and enhance new therapeutics' effectiveness. Models using simulators explore broad design spaces but risk violating implicit cons…
cs.DB2025
Learned Offline Query Planning via Bayesian Optimization
Jeffrey Tao, Natalie Maus, Haydn Jones +3
Analytics database workloads often contain queries that are executed repeatedly. Existing optimization techniques generally prioritize keeping optimization cost low, normally well…
cs.LG2025
Covering Multiple Objectives with a Small Set of Solutions Using Bayesian Optimization
Natalie Maus, Kyurae Kim, Yimeng Zeng +5
In multi-objective black-box optimization, the goal is typically to find solutions that optimize a set of black-box objective functions, , simultaneously. Trad…