Parallel Bayesian Optimization of Multiple Noisy Objectives with Expected Hypervolume Improvement

von Daulton, Samuel
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 3 of 36 (2022)

DIFFERENTIABLE EXPECTED HYPERVOLUME IMPROVEMENT FOR PARALLEL MULTI-OBJECTIVE BAYESIAN OPTIMIZATION

von Daulton, Samuel
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 12 of 27 (2021)

Log-Linear-Time Gaussian Processes Using Binary Tree Kernels

von Cohen, Michael K.
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 11 of 50 (2023)

Multi-Objective Bayesian Optimization Over High-dimensional Search Spaces

von Daulton, Samuel
Veröffentlicht in Conference on Uncertainty in Artificial Intelligence (38. : 2022 : Eindhoven) 38th Conference on Uncertainty in Artificial Intelligence (UAI 2022) ; Volume 1 of 3 (2023)

Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization

von Daulton, Samuel
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 17 of 50 (2023)

BOTORCH: A FRAMEWORK FOR EFFICIENT MONTE-CARLO BAYESIAN OPTIMIZATION

von Balandat, Maximilian
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 26 of 27 (2021)