SafeOpt
Optimization framework
An algorithmic framework for optimizing performance measures with safety constraints using Bayesian optimization and Gaussian processes.
Safe Bayesian Optimization
141 stars
8 watching
51 forks
Language: Python
last commit: almost 3 years ago
Linked from 1 awesome list
gaussian-processesoptimizationreinforcement-learningroboticssafety
krzjoa/awesome-python-data-scienceRelated projects:
| Repository | Description | Stars |
|---|---|---|
 automl/robo | A Bayesian optimization framework designed to optimize complex functions with robustness and flexibility | 484 |
 jonfanlab/glonet | A software framework for training neural networks to optimize dielectric metasurfaces using physics-driven generative models and global optimization algorithms. | 101 |
 acerbilab/bads | An optimization algorithm designed to fit computational models in the absence of gradient information or noisy objective functions. | 246 |
 jungtaekkim/bayeso | A framework for optimizing hyperparameters in machine learning models using Bayesian optimization | 93 |
 fpicetti/occamypy | A library for solving large-scale optimization problems with flexible and scalable vector and operator definitions | 55 |
 guopengf/auto-fedrl | A reinforcement learning-based framework for optimizing hyperparameters in distributed machine learning environments. | 15 |
 bluebrain/bluepyopt | A flexible framework for optimizing model parameters in computational neuroscience and related fields. | 204 |
 clementfarabet/lbfgs | An interface to a library providing a quasi-newton method for optimization problems | 2 |
 c-bata/goptuna | A decentralized hyperparameter optimization framework inspired by Optuna. | 262 |
 ccsi-toolset/foqus | A comprehensive framework for optimization and uncertainty quantification with support for surrogates and a graphical user interface. | 46 |
 pyomeca/bioptim | An optimization framework for biomechanics and control problems using multiple algorithms and libraries. | 94 |
 lucfra/far-ho | A package for optimizing hyperparameters and meta-learning using gradient-based methods in TensorFlow. | 188 |
 jiangoforit/yellowfin_pytorch | An optimizer that automatically tunes momentum and learning rate using local quadratic approximation. | 287 |
 litian96/fedprox | An optimization framework designed to address heterogeneity in federated learning across distributed networks | 655 |
 100/solid | A comprehensive framework for solving optimization problems without gradient calculations. | 575 |