dfm / gp
A tutorial about Gaussian process regression
☆185Updated 4 years ago
Alternatives and similar repositories for gp:
Users that are interested in gp are comparing it to the libraries listed below
- Deep Gaussian Processes in Python☆233Updated 3 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☆182Updated 10 years ago
- ☆232Updated 7 years ago
- GPz 2.0: Heteroscedastic Gaussian processes for uncertain and incomplete data☆49Updated 3 years ago
- Just a little MCMC☆222Updated 8 months ago
- A Primer on Gaussian Processes for Regression Analysis (PyData NYC 2019)☆166Updated 3 years ago
- InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy☆148Updated 7 months ago
- Additional kernels that can be used with scikit-learn's Gaussian Process module☆81Updated 8 months ago
- Manifold Markov chain Monte Carlo methods in Python☆226Updated last month
- Collection of jupyter notebooks for demonstrating software.☆165Updated last year
- Fast and flexible Gaussian Process regression in Python☆455Updated last week
- Kernel structure discovery research code - likely to be unstable☆190Updated 9 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆149Updated 6 years ago
- Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.☆249Updated 7 months ago
- pyGPs is a library containing an object-oriented python implementation for Gaussian Process (GP) regression and classification.☆214Updated 6 years ago
- Package implementing various parametric and nonparametric methods for conditional density estimation☆193Updated last year
- python version of the No-U-Turn Sampler (NUTS) from Hoffman & Gelman, 2011☆128Updated 4 years ago
- Deep GPs built on top of TensorFlow/Keras and GPflow☆124Updated 4 months ago
- Gaussian process modelling in Python☆222Updated 2 months ago
- Variational Autoencoder for Dimensionality Reduction of Time-Series☆187Updated 2 years ago
- Bayesian optimization for Python☆244Updated 3 years ago
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆232Updated last year
- Multi-Output Gaussian Process Toolkit☆170Updated 10 months ago
- ABCpy package☆113Updated 9 months ago
- ELFI - Engine for Likelihood-Free Inference☆272Updated 8 months ago
- Introduction to Uncertainty Quantification☆245Updated 2 years ago
- Implementing Bayes by Backprop☆183Updated 5 years ago
- Variational Fourier Features☆83Updated 3 years ago
- MCMC samplers for Bayesian estimation in Python, including Metropolis-Hastings, NUTS, and Slice☆335Updated 2 years ago
- Bayesian optimization☆37Updated 5 years ago