{"total":29,"rows":[{"id":"2111.13755","title":"A survey on multi-objective hyperparameter optimization algorithms for Machine Learning","created":"2021-11-23","cited_by_count":24,"area":null},{"id":"2304.11005","title":"Self-Correcting Bayesian Optimization through Bayesian Active Learning","created":"2023-04-21","cited_by_count":22,"area":null},{"id":"2111.03637","title":"Risk-averse Heteroscedastic Bayesian Optimization","created":"2021-11-05","cited_by_count":17,"area":null},{"id":"2201.12909","title":"Scaling Gaussian Process Optimization by Evaluating a Few Unique Candidates Multiple Times","created":"2022-01-30","cited_by_count":13,"area":null},{"id":"2112.07457","title":"Triangulation candidates for Bayesian optimization","created":"2021-12-14","cited_by_count":11,"area":null},{"id":"2206.05985","title":"Modeling the Machine Learning Multiverse","created":"2022-06-13","cited_by_count":11,"area":null},{"id":"2110.09334","title":"A portfolio approach to massively parallel Bayesian optimization","created":"2021-10-18","cited_by_count":9,"area":null},{"id":"2311.01195","title":"Batch Bayesian Optimization for Replicable Experimental Design","created":"2023-11-02","cited_by_count":8,"area":null},{"id":"2306.07299","title":"Additive Multi-Index Gaussian process modeling, with application to multi-physics surrogate modeling of the quark-gluon plasma","created":"2023-06-11","cited_by_count":6,"area":null},{"id":"2301.08789","title":"Active Learning of Piecewise Gaussian Process Surrogates","created":"2023-01-20","cited_by_count":5,"area":null},{"id":"2302.08612","title":"Robust expected improvement for Bayesian optimization","created":"2023-02-16","cited_by_count":5,"area":null},{"id":"2201.10239","title":"Design choice and machine learning model performances","created":"2022-01-25","cited_by_count":2,"area":null},{"id":"2102.07612","title":"Goal-oriented adaptive sampling under random field modelling of response probability distributions","created":"2021-02-15","cited_by_count":1,"area":null},{"id":"2204.10382","title":"Facilitating automated conversion of scientific knowledge into scientific simulation models with the Machine Assisted Generation, Calibration, and Comparison (MAGCC) Framework","created":"2022-04-21","cited_by_count":1,"area":null},{"id":"2207.03842","title":"Bayesian multi-objective optimization for stochastic simulators: an extension of the Pareto Active Learning method","created":"2022-07-08","cited_by_count":1,"area":null},{"id":"2405.10581","title":"Future Aware Safe Active Learning of Time Varying Systems using Gaussian Processes","created":"2024-05-17","cited_by_count":1,"area":null},{"id":"2412.07306","title":"Gearing Gaussian process modeling and sequential design towards stochastic simulators","created":"2024-12-10","cited_by_count":1,"area":null},{"id":"2209.04340","title":"Multi-objective hyperparameter optimization with performance uncertainty","created":"2022-09-09","cited_by_count":0,"area":null},{"id":"2312.04722","title":"Sensitivity Analysis in the Presence of Intrinsic Stochasticity for Discrete Fracture Network Simulations","created":"2023-12-07","cited_by_count":0,"area":null},{"id":"2406.07474","title":"Quantifying Local Model Validity using Active Learning","created":"2024-06-11","cited_by_count":0,"area":null},{"id":"2407.01495","title":"Multifidelity Cross-validation","created":"2024-07-01","cited_by_count":0,"area":null},{"id":"2504.20527","title":"Adaptive Replication Strategies in Trust-Region-Based Bayesian Optimization of Stochastic Functions","created":"2025-04-29","cited_by_count":0,"area":null},{"id":"2506.20928","title":"Active Learning for Manifold Gaussian Process Regression","created":"2025-06-26","cited_by_count":0,"area":null},{"id":"2508.16434","title":"Deep Intrinsic Coregionalization Multi-Output Gaussian Process Surrogate with Active Learning","created":"2025-08-22","cited_by_count":0,"area":null},{"id":"2511.13701","title":"Learning stochasticity: a nonparametric framework for intrinsic noise estimation","created":"2025-11-17","cited_by_count":0,"area":null},{"id":"2512.13530","title":"Actively Learning Joint Contours of Multiple Computer Experiments","created":"2025-12-15","cited_by_count":0,"area":null},{"id":"2604.20414","title":"Fast and Provably Accurate Sequential Designs using Hilbert Space Gaussian Processes","created":"2026-04-22","cited_by_count":0,"area":null},{"id":"2610.16801","title":"When Repeated Measurements Hurt Tabular Foundation Models","created":"2026-10-12","cited_by_count":0,"area":null},{"id":"2610.18434","title":"Principled Design of Expected Improvement for Continuous Simulation Optimization","created":"2026-10-13","cited_by_count":0,"area":null}],"next_cursor":null}