Diffusion Models (Currently in process):

We have trained a diffusion model to generate a simulated waveform from gaussian noise.

Demonstration:

Diffusion Model Predicting Noise (orange - noise, light green - predicted noise, dark green - intersection of the two)

Transformer + Cycle-GAN Models (Unpaired translation between simulated and detector waveforms)

Name		Name	Last commit message	Last commit date
Latest commit History 38 Commits
.ipynb_checkpoints		.ipynb_checkpoints
Eugi		Eugi
PU		PU
__pycache__		__pycache__
majorana		majorana
og		og
.gitignore		.gitignore
16_denoised_test_data.png		16_denoised_test_data.png
16_denoised_train_data.png		16_denoised_train_data.png
16_denoising_diffused_simulated_data.png		16_denoising_diffused_simulated_data.png
16_generated_from_noise.png		16_generated_from_noise.png
16_generating_from_noise.gif		16_generating_from_noise.gif
LICENSE		LICENSE
README.md		README.md
dataset.py		dataset.py
diffusion.py		diffusion.py
generate_w_diffusion.py		generate_w_diffusion.py
multiple_experiments.sh		multiple_experiments.sh
network.py		network.py
plot_and_save.py		plot_and_save.py
tools.py		tools.py
train.py		train.py
unit_test.ipynb		unit_test.ipynb