bayesian-optimisation

There are 15 repositories under bayesian-optimisation topic.

  • SMAC3

    automl/SMAC3

    SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

    Language:Python1.2k36607240

  • jajcayn/pygpso

    Gaussian-Processes Surrogate Optimisation in python

    Language:Python191111

  • eugene/prot-bo-0

    :pill: Guiding directed protein evolution with Bayesian Optimization - First Steps :pill:

    Language:Python16100
  • bayesopt-tutorial-r

    bearloga/bayesopt-tutorial-r

    Tutorial on Bayesian optimization in R

    Language:R15102

  • mikediessner/nubo

    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.

    Language:Python11110

  • lantonov/Optimisation

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

    Language:Python8513

  • ghanrabban/MATLAB-Bayesian-Optimized-Neural-Network-for-Laser-Amplifier

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

    Language:MATLAB7100

  • clear-nus/BOIRL

    Accompanying code of BO-IRL published in Neurips 2020

    Language:Python520

  • georgedeath/how-bayesian-should-BO-be

    How Bayesian should Bayesian Optimisation be?

    Language:Jupyter Notebook2100

  • JackBuck/decoupled-kg

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

    Language:Jupyter Notebook11

  • JBris/aws-botorch-torchx-nas

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

    Language:HTML110

  • JBris/bayesian-oed-opt-al

    Bayesian optimal experimental design, optimisation, and active learning with different acquisition functions

    Language:Jupyter Notebook1

  • mikediessner/environmental-conditions-BO

    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.

    Language:Python1100

  • MarioPasc/Coronary_Angiography_Detection

    Stenosis detection in Invasive Coronariography Angiography imaging

    Language:Python02

  • natthapong2100/demographic-linkage-active-learning

    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.

    Language:Jupyter Notebook