fonnesbeck / gp_regression
A Primer on Gaussian Processes for Regression Analysis (PyData NYC 2019)
☆165Updated 3 years ago
Alternatives and similar repositories for gp_regression:
Users that are interested in gp_regression are comparing it to the libraries listed below
- ☆231Updated 3 years ago
- ☆240Updated 6 years ago
- Just a little MCMC☆225Updated 9 months ago
- PyData London 2019 Tutorial on Markov chain Monte Carlo with PyMC3☆156Updated 5 years ago
- legend☆200Updated last year
- Gaussian process modelling in Python☆222Updated 4 months ago
- Examples of PyMC models, including a library of Jupyter notebooks.☆316Updated last week
- A tutorial about Gaussian process regression☆187Updated 4 years ago
- Statistical Rethinking (2nd Ed) with Tensorflow Probability☆270Updated 3 years ago
- Hidden Markov models in PyMC3☆99Updated last year
- Preparation materials for CEAi Precision Workshop #1 on Bayesian modelling☆58Updated 6 years ago
- Statistical Rethinking: A Bayesian Course Using Python and NumPyro☆90Updated 4 years ago
- A colourful collection of codes and notebooks, like Planet Sakaar☆55Updated 2 years ago
- Presented at Scipy Conference 2019☆126Updated 5 years ago
- Multi-Output Gaussian Process Toolkit☆172Updated last year
- Statistical Rethinking (2nd ed.) with NumPyro☆456Updated last year
- ☆231Updated 7 years ago
- ☆72Updated 6 years ago
- A collection of Bayesian data analysis recipes using PyMC3☆558Updated last year
- pymc-learn: Practical probabilistic machine learning in Python☆228Updated 4 years ago
- In which I try to demystify the fundamental concepts behind Bayesian deep learning.☆123Updated 7 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☆184Updated 10 years ago
- Exploring and eliciting probability distributions☆130Updated this week
- Bayesian Additive Regression Trees For Python☆223Updated last year
- Educational resources☆105Updated 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
- Material for ODSC Europe presentation -- Probabilistic Deep Learning in TensorFlow, the why and the how☆71Updated 5 years ago
- ☆158Updated 2 years ago
- Bayesian Analysis with Python - Second Edition, published by Packt☆133Updated 4 years ago
- Deep GPs built on top of TensorFlow/Keras and GPflow☆125Updated 6 months ago