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Experiments for PLDI 2019 submission on Gen
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Experiments for Gen, PLDI 2019

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

Structure of the repository

  • 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.

Basic instructions to set up the Julia environment

  1. Download and install Julia v1.1

  2. Clone git@github.com:probcomp/pldi2019-gen-experiments

  3. 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.

  4. Set the environment variable JULIA_PROJECT to the full path of this repository.

  5. Install dependencies using `julia -e 'using Pkg; Pkg.instantiate()'

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