mcleonard / sampyl
MCMC samplers for Bayesian estimation in Python, including Metropolis-Hastings, NUTS, and Slice
☆336Updated 2 years ago
Alternatives and similar repositories for sampyl:
Users that are interested in sampyl are comparing it to the libraries listed below
- ELFI - Engine for Likelihood-Free Inference☆272Updated 8 months ago
- Render probabilistic graphical models using matplotlib☆677Updated this week
- Just a little MCMC☆223Updated 8 months ago
- Kernel structure discovery research code - likely to be unstable☆189Updated 9 years ago
- A probabilistic programming system for simulators and high-performance computing (HPC), based on PyTorch☆390Updated 10 months ago
- Collection of jupyter notebooks for demonstrating software.☆166Updated last year
- Fast and flexible Gaussian Process regression in Python☆456Updated last week
- my blog☆266Updated 2 years ago
- Manifold Markov chain Monte Carlo methods in Python☆226Updated 2 months ago
- (Deprecated) Experimental PyMC interface for TensorFlow Probability. Official work on this project has been discontinued.☆712Updated 3 years ago
- python version of the No-U-Turn Sampler (NUTS) from Hoffman & Gelman, 2011☆127Updated 4 years ago
- ☆232Updated 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☆183Updated 10 years ago
- pymc-learn: Practical probabilistic machine learning in Python☆227Updated 4 years ago
- Statistical Rethinking with PyTorch and Pyro☆163Updated 5 years ago
- A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation☆128Updated 3 years ago
- ☆239Updated 6 years ago
- Bayesian Optimization using GPflow☆271Updated 4 years ago
- ABCpy package☆113Updated 10 months ago
- megaman: Manifold Learning for Millions of Points☆327Updated 2 years ago
- Python package for Bayesian Machine Learning with scikit-learn API☆517Updated 3 years ago
- pyGPs is a library containing an object-oriented python implementation for Gaussian Process (GP) regression and classification.☆214Updated 6 years ago
- Implementation in C and Theano of the method Probabilistic Backpropagation for scalable Bayesian inference in deep neural networks.☆192Updated 6 years ago
- Bayesian Python: Bayesian inference tools for Python☆697Updated 5 months ago
- PyStan, the Python interface to Stan☆924Updated 4 years ago
- InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy☆148Updated 7 months ago
- Python package for modular Bayesian optimization☆134Updated 4 years ago
- Personal project to compare hierarchical linear regression in PyMC3 and PyStan, as presented at http://pydata.org/london2016/schedule/pre…☆129Updated 8 years ago
- Additional kernels that can be used with scikit-learn's Gaussian Process module☆82Updated 8 months ago
- Python/PyMC3 versions of the programs described in Doing bayesian data analysis by John K. Kruschke☆899Updated 3 years ago