SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

Gaussian-Processes Surrogate Optimisation in python

💊 Guiding directed protein evolution with Bayesian Optimization - First Steps 💊

Tutorial on Bayesian optimization in R

NUBO is a Bayesian optimisation framework for the optimisation of expensive-to-evaluate black-box functions developed by the Fluid Dynamics Lab at Newcastle University.

Implementation of ROCK* algorithm (Gaussian kernel regression + natural gradient descent) for optimisation

MATLAB code of Bayesian Optimized Neural Network (BONN) for Gain Coefficient Estimation in Optical Fiber Laser Amplifier

Accompanying code of BO-IRL published in Neurips 2020

How Bayesian should Bayesian Optimisation be?

Data and code associated with paper "On the development of a practical Bayesian optimisation algorithm for expensive experiments and simulations with changing environmental conditions" currently in review.

Multi-objective Bayesian optimization with decoupled objectives using knowledge gradient and expectation over linear scalarisations

Testing submission of AWS batch jobs using BoTorch (via Ax) and TorchX for neural architecture search

Demographic linkage identifies individuals across historical documents. Traditional manual annotation of birth/death records is costly and time consuming. This project uses Active Learning to reduce labeling costs while maintaining accuracy, with Passive Learning as benchmark. Bayesian Optimization improves performance via hyperparameter tuning.

Stenosis detection in Invasive Coronariography Angiography imaging