SheffieldML / notebook
Collection of jupyter notebooks for demonstrating software.
☆167Updated 2 years ago
Alternatives and similar repositories for notebook:
Users that are interested in notebook are comparing it to the libraries listed below
- Additional kernels that can be used with scikit-learn's Gaussian Process module☆82Updated 10 months ago
- Clustering time series using Gaussian processes and Variational Bayes.☆39Updated 5 years ago
- Kernel structure discovery research code - likely to be unstable☆190Updated 9 years ago
- ☆233Updated 7 years ago
- ELFI - Engine for Likelihood-Free Inference☆274Updated this week
- Bayesian dessert for Lasagne☆84Updated 7 years ago
- ☆98Updated 7 years ago
- Bayesian Optimization using GPflow☆272Updated 4 years ago
- A Python package for Approximate Bayesian Computation☆36Updated 8 years ago
- Python package for modular Bayesian optimization☆135Updated 4 years ago
- Personal project to compare hierarchical linear regression in PyMC3 and PyStan, as presented at http://pydata.org/london2016/schedule/pre…☆128Updated 8 years ago
- Bayesian machine learning in Python☆76Updated 9 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
- PyMC3 codes of Lee and Wagenmakers' Bayesian Cognitive Modeling - A Pratical Course☆96Updated 7 years ago
- Collapsed Variational Bayes☆70Updated 5 years ago
- Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.☆249Updated 9 months ago
- Deep Gaussian Processes in matlab☆92Updated 3 years ago
- Bayesian optimization for Python☆245Updated 3 years ago
- bayesian bootstrapping in python☆121Updated 3 years ago
- A Gaussian process toolbox in python☆42Updated 13 years ago
- PyMC3 tutorial for DataScience LA (January 2017)☆67Updated 6 years ago
- ☆158Updated 2 years ago
- A tutorial about Gaussian process regression☆188Updated 4 years ago
- Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.☆82Updated 5 years ago
- ☆155Updated 5 years ago
- pyGPs is a library containing an object-oriented python implementation for Gaussian Process (GP) regression and classification.☆214Updated 6 years ago
- A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation☆128Updated 3 years ago
- Scikit-learn compatible estimation of general graphical models☆247Updated last year
- my blog☆267Updated 2 years ago
- megaman: Manifold Learning for Millions of Points☆327Updated 2 years ago