PredictiveScienceLab / py-mcmcLinks
A simple MCMC framework for training Gaussian processes adding functionality to GPy.
☆20Updated 11 years ago
Alternatives and similar repositories for py-mcmc
Users that are interested in py-mcmc are comparing it to the libraries listed below
Sorting:
- GPz 2.0: Heteroscedastic Gaussian processes for uncertain and incomplete data☆49Updated 4 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☆189Updated 11 years ago
- Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"☆26Updated 7 years ago
- Fast and flexible Gaussian Process regression in Python☆459Updated 3 weeks ago
- Proximal algorithms made easy in Python☆59Updated 8 years ago
- python version of the No-U-Turn Sampler (NUTS) from Hoffman & Gelman, 2011☆131Updated 5 years ago
- Hamiltonain Monte Carlo in Python☆40Updated 6 years ago
- Proximal optimization in pure python☆118Updated 3 years ago
- python-based shapelet decomposition package☆27Updated 8 years ago
- Deep Gaussian Processes in matlab☆93Updated 4 years ago
- Parameterization Framework for parameterized model creation and handling.☆49Updated 7 months ago
- Matlab code for the introduction to Gaussian processes, 2008☆30Updated 10 years ago
- Look Ahead Hamiltonian Monte Carlo☆30Updated 10 years ago
- Matlab code for my paper "Copula Variational Bayes inference via information geometry", submitted to IEEE Trans. on information theory, 2…☆57Updated 7 years ago
- A collection of Gaussian process models☆30Updated 8 years ago
- A Python convex optimization package using proximal splitting methods☆119Updated 4 months ago
- A tutorial about Gaussian process regression☆193Updated 5 years ago
- A Newton ADMM based solver for Cone programming.☆39Updated 8 years ago
- Gaussian mixture model for incomplete (missing or truncated) and noisy data☆104Updated 3 years ago
- Bayesian Dynamic Mode Decomposition (Bayesian DMD)☆18Updated 4 years ago
- Weighted Principal Component Analysis (PCA) in Python☆160Updated 8 years ago
- Parametric Gaussian Process Regression for Big Data☆45Updated 5 years ago
- Practice with MCMC methods and dynamics (Langevin, Hamiltonian, etc.)☆42Updated 5 years ago
- pyGPs is a library containing an object-oriented python implementation for Gaussian Process (GP) regression and classification.☆217Updated 7 years ago
- Code for paper "Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation"☆32Updated 6 years ago
- MCMC samplers for Bayesian estimation in Python, including Metropolis-Hastings, NUTS, and Slice☆341Updated 3 years ago
- Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.☆34Updated 8 years ago
- Additional kernels that can be used with scikit-learn's Gaussian Process module☆84Updated last year
- Gaussian processes with arbitrary derivative constraints and predictions.☆45Updated 6 years ago
- code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"☆417Updated last year