Machine learning, in numpy
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Updated
Oct 29, 2023 - Python
Machine learning, in numpy
Bayesian Modeling and Probabilistic Programming in Python
Deep universal probabilistic programming with Python and PyTorch
PyMC educational resources
A probabilistic programming library for Bayesian deep learning, generative models, based on Tensorflow
solution of exercises of the book "probabilistic robotics"
Stan development repository. The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.
Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.
Bayesian Data Analysis demos for Python
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
How to do Bayesian statistical modelling using numpy and PyMC3
Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code
RStan, the R interface to Stan
A Python library that helps data scientists to infer causation rather than observing correlation.
Learn about Machine Learning and Artificial Intelligence
Infer.NET is a framework for running Bayesian inference in graphical models
Fast and Easy Infinite Neural Networks in Python
Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
Solve and estimate Dynamic Stochastic General Equilibrium models (including the New York Fed DSGE)
Bayesian inference with probabilistic programming.
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