chrisstroemel / SimpleLinks
Experimental Global Optimization Algorithm
☆483Updated 7 years ago
Alternatives and similar repositories for Simple
Users that are interested in Simple are comparing it to the libraries listed below
Sorting:
- RoBO: a Robust Bayesian Optimization framework☆489Updated 6 years ago
- Artemis aims to get rid of all the boring, bureaucratic coding (plotting, file management, organizing experiments, etc) involved in machi…☆239Updated last year
- optimization routines for hyperparameter tuning☆424Updated 2 years ago
- Bayesian optimization for Python☆246Updated 3 years ago
- Bayesian Optimization using GPflow☆272Updated 5 years ago
- Tuning hyperparams fast with Hyperband☆597Updated 7 years ago
- InfiniteBoost: building infinite ensembles with gradient descent☆183Updated 7 years ago
- A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation☆128Updated 4 years ago
- Efficient Hyperparameter Optimization of Deep Learning Algorithms Using Deterministic RBF Surrogates☆115Updated 8 years ago
- A garden for scikit-learn compatible trees☆288Updated last year
- A fully decentralized hyperparameter optimization framework☆124Updated last year
- Python code for bayesian optimization using Gaussian processes☆314Updated 9 years ago
- A user-centered Python package for differentiable probabilistic inference☆203Updated 5 years ago
- Experimental Gradient Boosting Machines in Python with numba.☆189Updated 7 years ago
- An intelligent block matrix library for numpy, PyTorch, and beyond.☆310Updated last year
- Kernel structure discovery research code - likely to be unstable☆195Updated 10 years ago
- A simple, extensible library for developing AutoML systems☆175Updated 2 years ago
- Python package for Bayesian Machine Learning with scikit-learn API☆522Updated 4 years ago
- Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.☆251Updated last year
- Better, faster hyper-parameter optimization☆113Updated 2 years ago
- pyGPs is a library containing an object-oriented python implementation for Gaussian Process (GP) regression and classification.☆217Updated 6 years ago
- A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.☆273Updated 5 years ago
- A Python module for parallel optimization of expensive black-box functions☆446Updated 2 months ago
- Python package for modular Bayesian optimization☆136Updated 5 years ago
- Code for Mondrian Forests (for classification and regression)☆268Updated 9 years ago
- A Neural Networking library based on NumPy only☆113Updated 2 years ago
- Additional kernels that can be used with scikit-learn's Gaussian Process module☆84Updated last year
- A Python implementation of Jerome Friedman's Multivariate Adaptive Regression Splines☆469Updated 2 years ago
- a feature engineering wrapper for sklearn☆52Updated 5 years ago
- Future Gadget Laboratory☆221Updated 7 years ago