mcleonard / sampylLinks
MCMC samplers for Bayesian estimation in Python, including Metropolis-Hastings, NUTS, and Slice
☆339Updated 2 years ago
Alternatives and similar repositories for sampyl
Users that are interested in sampyl are comparing it to the libraries listed below
Sorting:
- ELFI - Engine for Likelihood-Free Inference☆277Updated 5 months ago
- Fast and flexible Gaussian Process regression in Python☆459Updated last week
- Render probabilistic graphical models using matplotlib☆683Updated last week
- A probabilistic programming system for simulators and high-performance computing (HPC), based on PyTorch☆389Updated last year
- Just a little MCMC☆232Updated last year
- Kernel structure discovery research code - likely to be unstable☆193Updated 10 years ago
- ☆240Updated 8 years ago
- Collection of jupyter notebooks for demonstrating software.☆169Updated 2 years ago
- megaman: Manifold Learning for Millions of Points☆331Updated 2 years ago
- Bayesian Optimization using GPflow☆272Updated 4 years ago
- my blog☆268Updated 3 years ago
- Manifold Markov chain Monte Carlo methods in Python☆233Updated last month
- python version of the No-U-Turn Sampler (NUTS) from Hoffman & Gelman, 2011☆132Updated 4 years ago
- Image Markov Chain Monte Carlo☆245Updated 3 years ago
- Additional kernels that can be used with scikit-learn's Gaussian Process module☆82Updated last year
- Python package for Bayesian Machine Learning with scikit-learn API☆521Updated 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☆187Updated 11 years ago
- Python package for modular Bayesian optimization☆137Updated 4 years ago
- Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.☆249Updated last year
- pyGPs is a library containing an object-oriented python implementation for Gaussian Process (GP) regression and classification.☆216Updated 6 years ago
- Sequential Monte Carlo working on top of pymc☆49Updated 6 years ago
- Likelihood-free inference toolbox.☆56Updated 8 years ago
- Implementation in C and Theano of the method Probabilistic Backpropagation for scalable Bayesian inference in deep neural networks.☆191Updated 6 years ago
- ABCpy package☆116Updated last year
- A tutorial about Gaussian process regression☆191Updated 5 years ago
- Scikit-learn compatible estimation of general graphical models☆248Updated 4 months ago
- A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation☆128Updated 4 years ago
- Express & compile probabilistic programs for performant inference on CPU & GPU. Powered by JAX.☆330Updated last year
- Pareto smoothed importance sampling (PSIS) and PSIS leave-one-out cross-validation for Python and Matlab/Octave☆77Updated last year
- ☆155Updated 6 years ago