TY - GEN
T1 - Basc
T2 - 33rd International Conference on Machine Learning, ICML 2016
AU - Carr, Shane
AU - Garnett, Roman
AU - Lo, Cynthia
PY - 2016
Y1 - 2016
N2 - We present a novel application of Bayesian optimization to the field of surface science: rapidly and accurately searching for the global minimum on potential energy surfaces. Controlling molecule-surface interactions is key for applications ranging from environmental catalysis to gas sensing. We present pragmatic techniques, including exploration/exploitation scheduling and a custom covariance kernel that encodes the properties of our objective function. Our method, the Bayesian Active Site Calculator (BASC), outperforms differential evolution and constrained minima hopping - two state-of-the-art approaches - in trial examples of carbon monoxide adsorption on a hematite substrate, both with and without a defect.
AB - We present a novel application of Bayesian optimization to the field of surface science: rapidly and accurately searching for the global minimum on potential energy surfaces. Controlling molecule-surface interactions is key for applications ranging from environmental catalysis to gas sensing. We present pragmatic techniques, including exploration/exploitation scheduling and a custom covariance kernel that encodes the properties of our objective function. Our method, the Bayesian Active Site Calculator (BASC), outperforms differential evolution and constrained minima hopping - two state-of-the-art approaches - in trial examples of carbon monoxide adsorption on a hematite substrate, both with and without a defect.
UR - https://www.scopus.com/pages/publications/84998678756
M3 - Conference contribution
AN - SCOPUS:84998678756
T3 - 33rd International Conference on Machine Learning, ICML 2016
SP - 1423
EP - 1432
BT - 33rd International Conference on Machine Learning, ICML 2016
A2 - Balcan, Maria Florina
A2 - Weinberger, Kilian Q.
PB - International Machine Learning Society (IMLS)
Y2 - 19 June 2016 through 24 June 2016
ER -