Pusula

Bayesian Optimization with GPyOpt

This post, we will expand on the concept of optimizing Bayesian Optimization with the GPyOpt library. What is a Gaussian Process? A Gaussian Process (GP) is a powerful mathematical framework used in ...
Pusula

A Multi-Agent Reinforcement Learning-Evolutionary and Bayesian Optimization: An example

This post is a follow-up on a series of combination of Deep Reinforcement Learning (DRL) and optimization methods to construct higher-performing ensemble portfolios. As in previous posts, we start ...
Nature

Accelerating cell culture media development using Bayesian optimization-based iterative experimental design

Optimizing operational conditions for complex biological systems used in life sciences research and biotechnology is an arduous task. Here, we apply a Bayesian Optimization-based iterative framework ...
Nature

Benchmarking the performance of Bayesian optimization across multiple experimental materials science domains

Bayesian optimization (BO) has been leveraged for guiding autonomous and high-throughput experiments in materials science. However, few have evaluated the efficiency of BO across a broad range of ...