Andrew C. Miller, Nicholas J. Foti, and Ryan P. Adams
Early version appearing in Advances in Approximate Bayesian Inference 2016 (NIPS Workshop)
Andrew C. Miller and Luke Bornn
Andrew Miller, Vishal Jain and Joseph L. Mundy
Simple, lightweight dynamic time warping implementation (and visualization) in numpy/python/cython.
A python module for astronomical source discovery and classification.
Sampyl is a package for sampling from probability distributions using MCMC methods. Similar to PyMC3 using theano to compute gradients, Sampyl uses autograd to compute gradients. However, you are free to write your own gradient functions, autograd is not necessary. This project was started as a way to use MCMC samplers by defining models purely with Python and numpy.