NYU data science project to simulate calorimeter readings using neural networks.
Charlie Guthrie (cdg356@nyu.edu), Israel Malkin (im965@nyu.edu), and Alex Pine (akp258@nyu.edu), under supervision from Prof. Kyle Cranmer (kyle.cranmer@nyu.edu).
| Name | Description | Location |
|---|---|---|
| Write-up | A paper describing our models and experiments | GenerativeModelsforHighEnergyPhysicsCalorimeters.pdf |
| Flat RNN Model | RNN model. Requires Keras 2.0. | scripts/rnn_flat/rnn_flat.py |
| MLP GAN Model | Simple MLP Wasserstein GAN model. Requires Keras 1.5. | scripts/spiral_gan/small.py |
| LAGAN Model | Location-Aware Wasserstein GAN model. Requires Keras 1.5. | scripts/spiral_gan/local.py |
| Data Loader | Code to load and clean the calorimeter data. | scripts/data_loader.py |
| Eval | Code to generate evaluation charts given a file of generated images. | scripts/eval.py |