lartpc_minkowski

Deep learning based LArTPC event reconstruction using MinkowskiEngine sparse convolution APIs.

This repository is an extension/update of DeepLearnPhysics/lartpc_mlreco3d using the StanfordVL/MinkowskiEngine generalized spatio-temporal sparse convolution library.

This repository uses the generalized sparse convolution library provided by StanfordVL:
Github Link: MinkowskiEngine
Paper (arXiv link): 4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networks

I. Contributing

1. Please keep the 80 column limit, unless absolutely necessary.

II. Repository Structure

• mlreco: contains all ML/DL algorithms for reconstructing LArTPC event.

• iotools:

• nn: shorthand for 'neural network'. This directory contains all neural network implementations that does not define a standalone model.

• models: contains all standalone models that could be trained by calling bin/run.py.

• post_processing: directory for post_processing algorithms, such as NMS and thresholding for PPN.

• utils: miscellaneous utility functions.

• bin:

• test: contains unit tests.

• config: configurations (*.cfg) files for training and validation.

III. Installation

We will use singularity containers to ship software.