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Hashing-Based Approximate Probabilistic Inference in Hybrid Domains
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PREREQUISITES: 

1) Z3 version 4.3.2: python binder https://github.com/Z3Prover/z3
2) Latte 1.6: binary https://www.math.ucdavis.edu/~latte/software.php


INSTALLATION:

> git clone https://github.com/vaishakbelle/APPROXWMI
> cd APPROXWMI/src 
> make 


RUNNING EXPERIMENTS:

> cd experiments/congestion
> unzip data/Se* -d data
> ln -s ../../bin/* .
> ./run.sh

CONTACTS:

Vaishak Belle <vaishak@cs.toronto.edu>
Guy Van den Broeck <guy.vandenbroeck@cs.kuleuven.be>
Andrea Passerini <passerini@disi.unitn.it>

Please cite APPROXWMI as:

Vaishak Belle, Guy Van den Broeck, Andrea Passerini. Hashing-Based Approximate Probabilistic Inference in Hybrid Domains, 
In Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence (UAI), 2015.

For license information, please refer to the file license.txt