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Tensorflow implementation for the interaction networks for boosted Higgs to bb tagger

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Interaction networks for the identification of boosted Higgs to bb decays

This is the Tensorflow 2.0 implementation of the interaction network model in E. Moreno et al., Interaction networks for the identification of boosted Higgs to bb decays, arXiv:1909.12285 [hep-ex]

For the original PyTorch implementation as well as plot-making functionality, please refer to https://github.com/eric-moreno/IN

Requirements

python 3.6
h5py 2.9.0
numpy 1.16.4
tensorflow-gpu 2.3.0-dev20200519 (this is the version I use)

Optional:

setGPU 0.0.7
gpustat 0.6.0

Training

Change the test_path and train_path in training.py to reflect the directories of the test and training datasets (in converted h5 format).

Determine the parameters needed for the IN. For example:

  • Output directory = IN_training
  • Vertex-vertex branch = 0 (turned off)
  • De = 20
  • Do = 24
  • Hidden = 60

Would be run as:

python3 training.py IN_training 0 --De 20 --Do 24 --hidden 60 

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Tensorflow implementation for the interaction networks for boosted Higgs to bb tagger

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