maka89 / noisy-gpLinks
Gaussian Process Regression for training data with noisy inputs and/or outputs
☆10Updated 8 years ago
Alternatives and similar repositories for noisy-gp
Users that are interested in noisy-gp are comparing it to the libraries listed below
Sorting:
- [ICML'18] Scalable Gaussian Processes with Grid-Structured Eigenfunctions☆20Updated 3 years ago
- Code for Kernel Adaptive Metropolis-Hastings☆33Updated 10 years ago
- Look Ahead Hamiltonian Monte Carlo☆30Updated 10 years ago
- Streaming sparse Gaussian process approximations☆69Updated 3 years ago
- Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.☆43Updated 11 years ago
- Variational Fourier Features☆86Updated 4 years ago
- Additional kernels that can be used with scikit-learn's Gaussian Process module☆84Updated last year
- Bayesian Gaussian mixture models in Python.☆64Updated 2 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- Python library for Recurrent Gaussian Processes☆22Updated 8 years ago
- A collection of Gaussian process models☆30Updated 8 years ago
- Deep Gaussian Processes in matlab☆93Updated 4 years ago
- Code for paper "Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation"☆32Updated 6 years ago
- Implementation of the Gaussian Process Autoregressive Regression Model☆68Updated 11 months ago
- Python implementation of the PR-SSM.☆56Updated 7 years ago
- Bayesian optimization in high-dimensions via random embedding.☆116Updated 12 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆151Updated 6 years ago
- Bayesian optimization☆38Updated 6 years ago
- Differentiable Gaussian Process implementation for PyTorch☆22Updated 7 years ago
- FALKON implementation used in the experimental section of "FALKON: An Optimal Large Scale Kernel Method"☆30Updated 5 years ago
- pyGPs is a library containing an object-oriented python implementation for Gaussian Process (GP) regression and classification.☆217Updated 6 years ago
- Various estimators of the infinite dimensional exponential family model☆16Updated 8 years ago
- Experiment code for Stochastic Gradient Hamiltonian Monte Carlo☆109Updated 7 years ago
- Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.☆34Updated 8 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference