ebonilla / mtgp
Multi-task Gaussian Process
☆43Updated 9 years ago
Alternatives and similar repositories for mtgp:
Users that are interested in mtgp are comparing it to the libraries listed below
- Max-value Entropy Search for Efficient Bayesian Optimization☆71Updated 2 years ago
- Multiple output Gaussian processes in MATLAB including the latent force model.☆49Updated 9 years ago
- Additive Gaussian Process Bandits - version 1.0☆26Updated 8 years ago
- Deep Gaussian Processes in matlab☆91Updated 3 years ago
- Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.☆31Updated 7 years ago
- Batched High-dimensional Bayesian Optimization via Structural Kernel Learning☆14Updated 6 years ago
- Streaming sparse Gaussian process approximations☆62Updated 2 years ago
- see https://github.com/thangbui/geepee for a faster implementation☆37Updated 7 years ago
- Deep Kernel Learning. Gaussian Process Regression where the input is a neural network mapping of x that maximizes the marginal likelihood☆94Updated 7 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆148Updated 5 years ago
- Heterogeneous Multi-output Gaussian Processes☆51Updated 4 years ago
- The High-dimensional BayesOpt algorithms from "A Framework for Bayesian Optimization in Embedded Subspaces☆40Updated 5 years ago
- Bayesian optimization in high-dimensions via random embedding.☆113Updated 11 years ago
- Variational Gaussian Process State-Space Models☆23Updated 9 years ago
- Parametric Gaussian Process Regression for Big Data☆44Updated 4 years ago
- Matlab implementations of Gaussian processes and other machine learning tools.☆136Updated 7 years ago
- Deep Gaussian Processes in Python☆232Updated 3 years ago
- Unifying sparse approximations for Gaussian process regression and classification, using Power EP☆22Updated 8 years ago
- Multi-fidelity Gaussian Process Bandit Optimisation☆39Updated 8 years ago
- ☆40Updated 5 years ago
- Variational Inference in Gaussian Mixture Model☆58Updated 4 years ago
- We use a modified neural network instead of Gaussian process for Bayesian optimization.☆108Updated 7 years ago
- A framework for Bayesian optimization of composite functions.☆14Updated 2 years ago
- ☆28Updated 5 years ago
- Bayesian optimization with the Gaussian process assumption☆30Updated 8 years ago
- code for "Efficient Optimization for Sparse Gaussian Process Regression"☆21Updated 11 years ago
- multivariate Gaussian process regression and multivariate Student-t process regression☆70Updated 3 years ago
- An implementation of "ADMMBO, An ADMM Framework for Bayesian Optimization with Unknown Constraints''☆21Updated 5 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆38Updated 5 years ago
- Library for Deep Gaussian Processes based on GPflow☆19Updated 4 years ago