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Black box variational inference for state space models

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Black box variational inference for state space models

Reference implementation of the algorithms described in the following publications:

Y Gao*, E Archer*, L Paninski, J Cunningham (2016). Linear dynamical neural population models through nonlinear embeddings

E Archer, IM Park, L Buesing, J Cunningham, L Paninski (2015). Black box variational inference for state space models

Tutorial

An IPython Notebook tutorial is available in the code directory:

https://github.com/earcher/vilds/blob/master/code/tutorial.ipynb

Installation

To check out, run git@github.com:earcher/vilds.git

The code is written in Python 2. In addition to standard scientific Python libraries (IPython, numpy, matplotlib), the code expects:

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