409 citations · 3.5k across the 48 of their papers we have counts for
49 papers
Optimizing over trained GNNs via symmetry breaking
Shiqiang Zhang, Juan S. Campos, Christian Feldmann +5
Optimization over trained machine learning models has applications including: verification, minimizing neural acquisition functions, and integrating a trained surrogate into a larg…
Combining Multi-Fidelity Modelling and Asynchronous Batch Bayesian Optimization
Jose Pablo Folch, Robert M Lee, Behrang Shafei +4
Bayesian Optimization is a useful tool for experiment design. Unfortunately, the classical, sequential setting of Bayesian Optimization does not translate well into laboratory expe…
Tree ensemble kernels for Bayesian optimization with known constraints over mixed-feature spaces
Alexander Thebelt, Calvin Tsay, Robert M. Lee +4
Tree ensembles can be well-suited for black-box optimization tasks such as algorithm tuning and neural architecture search, as they achieve good predictive performance with little…
SnAKe: Bayesian Optimization with Pathwise Exploration
Jose Pablo Folch, Shiqiang Zhang, Robert M Lee +5
Bayesian Optimization is a very effective tool for optimizing expensive black-box functions. Inspired by applications developing and characterizing reaction chemistry using droplet…
Multi-Objective Constrained Optimization for Energy Applications via Tree Ensembles
Alexander Thebelt, Calvin Tsay, Robert M. Lee +4
Energy systems optimization problems are complex due to strongly non-linear system behavior and multiple competing objectives, e.g. economic gain vs. environmental impact. Moreover…
CRPropa - A Toolbox for Cosmic Ray Simulations
R. Alves Batista, J. Becker Tjus, A. Dundovic +11
The astrophysical interpretation of recent experimental observations of cosmic rays relies increasingly on Monte Carlo simulations of cosmic ray propagation and acceleration. Depen…