Extensions of Bayesian Optimization for Real-World Applications

Bayesian Optimization with Robust Bayesian Neural Networks

Bayesian optimization is a method used to optimize complex functions that are expensive or time-consuming to evaluate. It is widely applied in machine learning, engineering, and scientific research to improve efficiency and precision, particularly in scenarios like hyperparameter tuning and experimental design. ✔️ Efficient Function Evaluation: Bayesian optimization minimizes costly evaluations, making it ideal for scenarios where each evaluation has a high resource cost. ✔️ Versatility: It hand

Learning with Gaussian Processes