Samuel Daulton
Menlo School(US)
Publications by Year
Research Areas
Advanced Bandit Algorithms Research, Advanced Multi-Objective Optimization Algorithms, Machine Learning and Data Classification, Gaussian Processes and Bayesian Inference, Optimal Experimental Design Methods
Most-Cited Works
- → BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization(2019)203 cited
- → Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization(2020)121 cited
- → Parallel Bayesian Optimization of Multiple Noisy Objectives with\n Expected Hypervolume Improvement(2021)92 cited
- BoTorch: Programmable Bayesian Optimization in PyTorch.(2019)
- → Unexpected Improvements to Expected Improvement for Bayesian Optimization(2023)43 cited
- → Multi-Objective Bayesian Optimization over High-Dimensional Search\n Spaces(2021)24 cited
- → Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization(2022)16 cited
- → Thompson Sampling for Contextual Bandit Problems with Auxiliary Safety\n Constraints(2019)8 cited