adler-j

learned_primal_dual

Learned Primal-Dual Reconstruction

learned_gradient_tomography

Solving ill-posed inverse problems using iterative deep neural networks

minimal_wgan

A minimal implementation of Wasserstein GAN

minimal_vae

A minimal implementation of an Variational Auto-Encoder

bwgan

Code for the paper "Banach Wasserstein GAN"

tfdeform

Utilities to create random deformations in tensorflow

adler

General python utilities

goettingen_dl_course_2018

Deep Learning course in Göttingen April 2018

multiscale_dense

Efficient implementation of multiscale dense networks

deep_bayesian_inversion

invertible_gln

odl

Operator Discretization Library

tensordata

Public datasets for Tensorflow

academic-kickstart

academic-kickstart-1

Easily create a beautiful website using Academic and Hugo

academic_website

Source code for my personal webpage

ad-skull-reconstruction

Repository for reconstruction of simulated skull CT data for AD project

adler-j.github.io

My personal webpage

batchgenerators

A framework for data augmentation for 2D and 3D image classification and segmentation

cv

my curriculum vitae

docker-stacks

Opinionated stacks of ready-to-run Jupyter applications in Docker.

fastMRI

A large-scale dataset of both raw MRI measurements and clinical MRI images

jax

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

minimal_cyclegan

minimal_progressive_gan

A minimal implementation of Progressive GAN for MNIST

msd_pytorch

A Pytorch implementation of the mixed-scale dense network described in https://doi.org/10.1073/pnas.1715832114

odlworkshop

Repository moved to https://github.com/odlgroup/odlworkshop

pydicom

Automatically exported from code.google.com/p/pydicom

pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

tensorflow-build

TensorFlow binaries supporting AVX, FMA, SSE