AmpersandTV / pymc3-hmmLinks
Hidden Markov models in PyMC3
☆99Updated last year
Alternatives and similar repositories for pymc3-hmm
Users that are interested in pymc3-hmm are comparing it to the libraries listed below
Sorting:
- ☆73Updated 6 years ago
- A colourful collection of codes and notebooks, like Planet Sakaar☆55Updated 2 years ago
- Powerful add-ons for PyMC☆106Updated last week
- ☆121Updated last week
- Generalized additive models in Python with a Bayesian twist☆78Updated last year
- Simulation based calibration and generation of synthetic data.☆55Updated 3 weeks ago
- Bayesian Regression Models in Pyro☆72Updated 11 months ago
- Educational resources☆104Updated 3 years ago
- Gaussian Process Model Building Interface☆51Updated 4 months ago
- Exploring and eliciting probability distributions☆139Updated 3 weeks ago
- ☆41Updated 3 years ago
- Formulas for mixed-effects models in Python☆61Updated 5 months ago
- Inference case studies in jupyter☆93Updated 6 years ago
- ☆240Updated 7 years ago
- bayes-toolbox☆93Updated last week
- Source repository for the online book Exploratory Analysis of Bayesian Models.☆24Updated 2 weeks ago
- Python wrapper for nuts-rs☆162Updated last week
- Presented at Scipy Conference 2019☆127Updated 5 years ago
- In which I play with the ideas surrounding causality☆53Updated 2 years ago
- ☆90Updated 4 years ago
- pymc-learn: Practical probabilistic machine learning in Python☆230Updated 4 years ago
- Implementation of Hidden Markov Models in pymc3☆61Updated 8 years ago
- Statistical Rethinking: A Bayesian Course Using Python and NumPyro☆90Updated 4 years ago
- Randomization-based inference in Python☆81Updated last week
- Bayesian Conjugate Models in Python☆31Updated last week
- A system for Bayesian estimation of state space models using PyMC☆33Updated last year
- ☆159Updated 2 years ago
- Examples of PyMC models, including a library of Jupyter notebooks.☆339Updated last week
- Preparation materials for CEAi Precision Workshop #1 on Bayesian modelling☆58Updated 7 years ago
- An interactive visualization tool that transforms probabilistic programming models into an "Interactive Probabilistic Models Explorer".☆24Updated last year