GPflow / GPflowOpt
Bayesian Optimization using GPflow
☆270Updated 4 years ago
Alternatives and similar repositories for GPflowOpt:
Users that are interested in GPflowOpt are comparing it to the libraries listed below
- RoBO: a Robust Bayesian Optimization framework☆485Updated 5 years ago
- A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.☆266Updated 5 years ago
- Bayesian optimization for Python☆243Updated 3 years ago
- Gaussian Process Optimization using GPy☆938Updated 2 years ago
- ☆232Updated 7 years ago
- Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.☆249Updated 7 months ago
- Python package for modular Bayesian optimization☆134Updated 4 years ago
- Bayesian neural network package☆141Updated 3 years ago
- BayesOpt: A toolbox for bayesian optimization, experimental design and stochastic bandits.☆405Updated last year
- InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy☆148Updated 7 months ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆148Updated 6 years ago
- Bayesian optimization in high-dimensions via random embedding.☆113Updated 11 years ago
- Python code for bayesian optimization using Gaussian processes☆311Updated 8 years ago
- Deep Gaussian Processes in Python☆233Updated 3 years ago
- pyGPs is a library containing an object-oriented python implementation for Gaussian Process (GP) regression and classification.☆214Updated 6 years ago
- A Bayesian optimization toolbox built on TensorFlow☆227Updated this week
- Deep GPs built on top of TensorFlow/Keras and GPflow☆124Updated 4 months ago
- Structurally efficient multi-output linearly coregionalized Gaussian Processes: it's tricky, tricky, tricky, tricky, tricky.☆37Updated 2 years ago
- Collection of jupyter notebooks for demonstrating software.☆165Updated last year
- Additional kernels that can be used with scikit-learn's Gaussian Process module☆81Updated 7 months ago
- Gaussian processes in TensorFlow☆1,863Updated 2 weeks ago
- optimization routines for hyperparameter tuning☆418Updated last year
- We use a modified neural network instead of Gaussian process for Bayesian optimization.☆108Updated 7 years ago
- Benchmark framework to easily compare Bayesian optimization methods on real machine learning tasks☆143Updated 3 years ago
- A probabilistic programming system for simulators and high-performance computing (HPC), based on PyTorch☆391Updated 9 months ago
- ☆69Updated 4 years ago
- Kernel structure discovery research code - likely to be unstable☆190Updated 9 years ago
- I am in [research] stepped in so far that, should I wade no more, Returning were as tedious as go o'er. -MacBeth☆181Updated 10 years ago
- Surrogate Optimization Toolbox for Python☆205Updated 3 years ago
- Domain specific language for configuration spaces in Python. Useful for hyperparameter optimization and algorithm configuration.☆207Updated 3 months ago