| ALE: a generic assembly likelihood evaluation framework for assessing the accuracy of genome and metagenome assemblies SC Clark, R Egan, PI Frazier, Z Wang Bioinformatics 29 (4), 435-443, 2013 | 195 | 2013 |
| Parallel Bayesian global optimization of expensive functions J Wang, SC Clark, E Liu, PI Frazier arXiv preprint arXiv:1602.05149, 2016 | 111 | 2016 |
| Bayesian optimization for machine learning: A practical guidebook I Dewancker, M McCourt, S Clark arXiv preprint arXiv:1612.04858, 2016 | 98 | 2016 |
| Parallel Bayesian global optimization of expensive functions J Wang, SC Clark, E Liu, PI Frazier Operations Research 68 (6), 1850-1865, 2020 | 82 | 2020 |
| Bayesian optimization primer I Dewancker, M McCourt, S Clark URL https://app. sigopt. com/static/pdf/SigOpt_ Bayesian_Optimization_Primer …, 2015 | 68 | 2015 |
| A stratified analysis of Bayesian optimization methods I Dewancker, M McCourt, S Clark, P Hayes, A Johnson, G Ke arXiv preprint arXiv:1603.09441, 2016 | 45 | 2016 |
| Systems and methods implementing an intelligent optimization platform P Hayes, M McCourt, A Johnson, G Ke, S Clark US Patent 10,217,061, 2019 | 32 | 2019 |
| A strategy for ranking optimization methods using multiple criteria I Dewancker, M McCourt, S Clark, P Hayes, A Johnson, G Ke Workshop on Automatic Machine Learning, 11-20, 2016 | 30 | 2016 |
| Sigopt web page S Clark, P Hayes SigOpt Web Page, 2019 | 27 | 2019 |
| Systems and methods for implementing an intelligent application program interface for an intelligent optimization platform A Johnson, P Hayes, S Clark US Patent 10,282,237, 2019 | 20 | 2019 |
| Parallel global optimization using an improved multi-points expected improvement criterion PI Frazier, SC Clark INFORMS Optimization Society Conference, Miami FL 26, 2012 | 19 | 2012 |
| Bayesian Optimization Primer. 2015 I Dewancker, M McCourt, S Clark URL: https://static. sigopt. com/b/20a144d208ef255d3b981ce419667ec25d8412e2 …, 2013 | 17 | 2013 |
| Systems and methods for implementing an intelligent machine learning optimization platform for multiple tuning criteria B Cheng, O Kim, M McCourt, P Hayes, S Clark US Patent 10,528,891, 2020 | 13 | 2020 |
| Evaluation system for a bayesian optimization service I Dewancker, M McCourt, S Clark, P Hayes, A Johnson, G Ke arXiv preprint arXiv:1605.06170, 2016 | 13 | 2016 |
| Systems and methods for implementing an intelligent machine learning optimization platform for multiple tuning criteria B Cheng, O Kim, M McCourt, P Hayes, S Clark US Patent 10,558,934, 2020 | 12 | 2020 |
| MOE: A global, black box optimization engine for real world metric optimization S Clark, E Liu, P Frazier, JL Wang, D Oktay, N Vesdapunt MOE: A global, black box optimization engine for real world metric optimization, 2014 | 12 | 2014 |
| Tuning Shear Thinning Factors of 3D Bio-Printable Hydrogels Using Short Fiber S Tuladhar, S Clark, A Habib Materials 16 (2), 572, 2023 | 11 | 2023 |
| Systems and methods implementing an intelligent optimization platform P Hayes, M McCourt, A Johnson, G Ke, S Clark US Patent 10,607,159, 2020 | 11 | 2020 |
| Systems and methods for implementing an intelligent application program interface for an intelligent optimization platform A Johnson, P Hayes, S Clark US Patent 10,445,150, 2019 | 10 | 2019 |
| Systems and methods implementing an intelligent machine learning tuning system providing multiple tuned hyperparameter solutions K Tee, M McCourt, P Hayes, S Clark US Patent 11,270,217, 2022 | 9 | 2022 |
