One-bit compressed sensing using generative models

This repository consists of the code used for the numerical experiments in the master's thesis "One-bit compressed sensing using generative models".

Name		Name	Last commit message	Last commit date
Latest commit History 7 Commits
results_data		results_data
results_images		results_images
.gitignore		.gitignore
1_MNIST_BIHT_vs_Regularized.ipynb		1_MNIST_BIHT_vs_Regularized.ipynb
2_MNIST_BIHT_Images.ipynb		2_MNIST_BIHT_Images.ipynb
3_MNIST_BIHT_complexity_tradeoff.ipynb		3_MNIST_BIHT_complexity_tradeoff.ipynb
4_multi_model_reconstruction.ipynb		4_multi_model_reconstruction.ipynb
5_MNIST_dithering_sparse_Haar_generative.ipynb		5_MNIST_dithering_sparse_Haar_generative.ipynb
6_MNIST_optimal_regularization.ipynb		6_MNIST_optimal_regularization.ipynb
7_CIFAR_dithering_comparison.ipynb		7_CIFAR_dithering_comparison.ipynb
8_CIFAR_noise.ipynb		8_CIFAR_noise.ipynb
9_CIFAR_heavy_tailed_measurements.ipynb		9_CIFAR_heavy_tailed_measurements.ipynb
CIFAR10_generative.py		CIFAR10_generative.py
CIFAR10_utils.py		CIFAR10_utils.py
MNIST_generative.py		MNIST_generative.py
MNIST_utils.py		MNIST_utils.py
README.md		README.md
general_utils.py		general_utils.py
sparsity_utils.py		sparsity_utils.py

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