{"total":13,"rows":[{"id":"2410.16893","title":"Global Optimization of Gaussian Process Acquisition Functions Using a Piecewise-Linear Kernel Approximation","created":"2024-10-22","cited_by_count":8,"area":null},{"id":"2510.03893","title":"BONSAI: Structure-exploiting robust Bayesian optimization for networked black-box systems under uncertainty","created":"2025-10-04","cited_by_count":5,"area":null},{"id":"2404.10949","title":"Human-Algorithm Collaborative Bayesian Optimization for Engineering Systems","created":"2024-04-16","cited_by_count":3,"area":null},{"id":"2406.02352","title":"System-Aware Neural ODE Processes for Few-Shot Bayesian Optimization","created":"2024-06-04","cited_by_count":3,"area":null},{"id":"2502.14121","title":"Multi-Objective Bayesian Optimization for Networked Black-Box Systems: A Path to Greener Profits and Smarter Designs","created":"2025-02-19","cited_by_count":3,"area":null},{"id":"2508.01834","title":"Efficient optimization of expensive black-box simulators via marginal means, with application to neutrino detector design","created":"2025-08-03","cited_by_count":2,"area":null},{"id":"2512.17659","title":"Generative Multi-Objective Bayesian Optimization with Scalable Batch Evaluations for Sample-Efficient De Novo Molecular Design","created":"2025-12-19","cited_by_count":2,"area":null},{"id":"2603.11199","title":"Bayesian Optimization of Partially Known Systems using Hybrid Models","created":"2026-03-11","cited_by_count":0,"area":null},{"id":"2605.00855","title":"An Efficient Spatial Branch-and-Bound Algorithm for Global Optimization of Gaussian Process Posterior Mean Functions","created":"2026-04-21","cited_by_count":0,"area":null},{"id":"2605.05382","title":"Meta-learning for sample-efficient Bayesian optimisation of fed-batch processes","created":"2026-05-06","cited_by_count":0,"area":null},{"id":"2607.04356","title":"How Many Initial Points Does Bayesian Optimization Need?","created":"2026-07-05","cited_by_count":0,"area":null},{"id":"2609.17440","title":"Reduced-Space Multi-Fidelity Bayesian Optimization of Process Simulation Models","created":"2026-09-15","cited_by_count":0,"area":null},{"id":"2610.02014","title":"Atoms to Processes: The Role of Artificial Intelligence and Machine Learning in Chemical Engineering","created":"2026-10-01","cited_by_count":0,"area":null}],"next_cursor":null}