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Hit Identification inside SuperFGD with Transformers

Basic use

  • To run the baseline configuration, run: python main.py -f "config/baseline.yaml"

-To run in test mode, simply add a -t argument above.

Overview

  • config holds the different configuration files for training and testing.
  • data holds several files for data handling, Lightning DataModule creation and preprocessing.
  • models contains the main engine in engine_nodecl.py and the different variants of transformer encoders that have been tested in transformer_encoder.py
  • notebooks gives notebooks to illustrate the work. In sfgd_eda.ipynb you'll basic data analysis on the dataset. model_inference.ipynb displays attention maps and the model predictions compared to the ground truth. umap_embedding.ipynb applies the UMAP dimensionality reduction on the last layer output of the model (before the linear classifier).

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