Mocapy++ / News: Recent posts

Mocapy is a toolkit for learning and inference in Dynamic Bayesian Networks, implemented in Python.
Version 0.726 has some small bug fixes, mostly related to the recent numpy migration.

Mocapy is a toolkit for learning and inference in Dynamic Bayesian Networks. Release 0.725 contains a number of small bug fixes.

Mocapy is a parallelized toolkit for learning and inference
in Dynamic Bayesian Networks, implemented in Python.
Version 0.681 features various bug fixes and optimizations,
better Viterbi and Smoothing support and a new method
to sample from a Kent node.

Mocapy is a parallelized toolkit for learning and inference in Dynamic Bayesian Networks. This is its first, very preliminary release.