This repository contains the code for figures and experiments appearing in
Marco F. Cusumano-Towner, Feras A. Saad, Alex Lew, and Vikash K. Mansinghka. 2019. Gen: A General-Purpose Probabilistic Programming System with Programmable Inference. To Appear In Proceedings of 39th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI'19). ACM, New York, NY, USA
- example contains the code for the tutorial in Figure 2.
- regression contains the code for the robust Bayesian regression benchmark in Section 7.1.
- gp contains the code for the Gaussian process structure benchmark in Section 7.2.
- algorithmic-model contains the code for the algorithmic model of an autonomous agent in Section 7.3.
- state-space contains the code for the nonlinear state-space model in Section 7.4.
- pose contains the code of the pose estimation application in Section 7.5.
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Download and install Julia v1.1
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Clone
[email protected]:probcomp/pldi2019-gen-experiments
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Run
export JULIA_PROJECT=/path/to/pldi2019-gen-experiments
, where/path/to
should be the prefix of the absolute path of this repository on your local disk. -
Set the environment variable
JULIA_PROJECT
to the full path of this repository. -
Install dependencies using `julia -e 'using Pkg; Pkg.instantiate()'