adler-j/minimal_wgan

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Python
License
MIT License
Created about 7 years ago
Updated about 7 years ago

adler-j/minimal_wgan

adler-j

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A minimal implementation of Wasserstein GAN

learned_primal_dual

Learned Primal-Dual Reconstruction

learned_gradient_tomography

Solving ill-posed inverse problems using iterative deep neural networks

minimal_vae

A minimal implementation of an Variational Auto-Encoder

bwgan

Code for the paper "Banach Wasserstein GAN"

wasserstein_inverse_problems

Code for the article "Learning to solve inverse problems using Wasserstein loss"

tfdeform

Utilities to create random deformations in tensorflow

adler

General python utilities

mfcm_article

Code for the paper "A modified fuzzy C means algorithm for shading correction in craniofacial CBCT images"

spectral_ct_examples

odl-stem-examples

Examples of STEM tomography using ODL

GPUMC

Mirror from google code https://code.google.com/archive/p/mcgpu/

multiscale_dense

Efficient implementation of multiscale dense networks

goettingen_dl_course_2018

Deep Learning course in Göttingen April 2018

Jupyter Notebook

lie_grp_diffeo

Diffeomorphisms based on lie groups

deep_bayesian_inversion

learned_matrix_inverse_problems

invertible_gln

tensordata

Public datasets for Tensorflow