jmetzen / bayesian_optimizationLinks
Bayesian optimization
☆38Updated 5 years ago
Alternatives and similar repositories for bayesian_optimization
Users that are interested in bayesian_optimization are comparing it to the libraries listed below
Sorting:
- Additional kernels that can be used with scikit-learn's Gaussian Process module☆82Updated last year
- I am in [research] stepped in so far that, should I wade no more, Returning were as tedious as go o'er. -MacBeth☆186Updated 11 years ago
- Reference implementation of Optimistic Expected Improvement.☆50Updated 5 years ago
- A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.☆270Updated 5 years ago
- Bayesian optimization for Python☆246Updated 3 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆151Updated 6 years ago
- Bayesian optimization in high-dimensions via random embedding.☆115Updated 12 years ago
- ☆239Updated 8 years ago
- Deep Gaussian Processes in Python☆236Updated 4 years ago
- Bayesian Optimization using GPflow☆272Updated 4 years ago
- Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.☆248Updated last year
- Parallelised Thompson Sampling in GPs for Bayesian Optimisation☆36Updated 8 years ago
- Deep Gaussian Processes in matlab☆93Updated 4 years ago
- [ICML'18] Scalable Gaussian Processes with Grid-Structured Eigenfunctions☆20Updated 3 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆73Updated 4 years ago
- Differentiable Gaussian Process implementation for PyTorch☆22Updated 7 years ago
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- Parameterization Framework for parameterized model creation and handling.☆49Updated 3 months ago
- Bayesian neural network package☆151Updated 4 years ago
- Convolutional Gaussian processes based on GPflow.☆95Updated 7 years ago
- A tutorial about Gaussian process regression☆189Updated 5 years ago
- pyGPs is a library containing an object-oriented python implementation for Gaussian Process (GP) regression and classification.☆216Updated 6 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆39Updated 6 years ago
- Entropy Search for Information-Efficient Global Optimization - JMLR v13☆30Updated 8 years ago
- Deep GPs built on top of TensorFlow/Keras and GPflow☆127Updated 11 months ago
- ☆40Updated 6 years ago
- Python implementation of the PR-SSM.☆55Updated 7 years ago
- see https://github.com/thangbui/geepee for a faster implementation☆37Updated 8 years ago
- Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.☆141Updated 9 years ago
- Neural Processes implementation for 1D regression☆64Updated 6 years ago