numpyro
cookiecutter-pystan
numpyro | cookiecutter-pystan | |
---|---|---|
2 | 1 | |
2,046 | 0 | |
1.1% | - | |
8.7 | 4.0 | |
about 12 hours ago | 4 months ago | |
Python | Python | |
Apache License 2.0 | - |
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numpyro
- Bayesian Analysis with Python
-
Saving the World with Bayesian Modeling
Perhaps an alternative to look into: Numpyro [1] has a JAX backend so can be really fast when compiled; and it can run on GPUs. So that might be helpful for your problem with loads of data.
[1] https://github.com/pyro-ppl/numpyro
cookiecutter-pystan
-
Bayesian Analysis with Python
Self plug for stan on windows in a docker dev environment:
https://github.com/dbonattoj/cookiecutter-pystan
What are some alternatives?
PyMC - Bayesian Modeling and Probabilistic Programming in Python
pymc-resources - PyMC educational resources
trax - Trax — Deep Learning with Clear Code and Speed
Statistical-Rethinking-with-Python-and-PyMC3 - Python/PyMC3 port of the examples in " Statistical Rethinking A Bayesian Course with Examples in R and Stan" by Richard McElreath
einops - Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
Statistical-Rethinking-with-P
pyprobml - Python code for "Probabilistic Machine learning" book by Kevin Murphy
BayesianEcosystems_IAP - Notes and code for Bayesian ecosystem modeling IAP course
Bayeslite - BayesDB on SQLite. A Bayesian database table for querying the probable implications of data as easily as SQL databases query the data itself.
datasets - TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...
MultiBUGS - Multi-core BUGS for fast Bayesian inference of large hierarchical models
adaptive-policy-iteration - JAX implementation of Adaptive Approximate Policy Iteration (Hao et al., 2021)