GitLab

Samples and documentation for the "Getting started with Deep Learning on Supercomputers" tutorial.

Simulation module

The tutorial has been moved to: https://gitlab.version.fz-juelich.de/hpc4ns/dl_on_supercomputers

a tool to enable fast and flexible Machine Learning on Air data time series

Reporting module

Visualization module

Framework for simulating pedestrians with state of the art models.

ParaViewWeb RemoteRenderer in Jupyter

Sparse Matrix Generator with Given Spectrum

Homepage: https://smg2s.github.io

Run Zhang Master Thesis. Title: "Super-Resolution of Sentinel-2 Images with Generative Adversarial Networks". 2020

Enhancing Resolution of Sentinel 2 Hyperspectral Satellite Images with Super-resolution Generative Adversarial Networks

A library of Python utilities developed at the Simulation and Data Laboratory Neuroscience, and the High Performance Computing in Neuroscience (HPCNS) division of the Jülich Supercomputing Center.

Here is the repository of the on-going project to develop a stand-alone sager with Python to using for I/O, Pre/Post-Processing

Wiki for material and resources, Deep Learning for COVID XRay detection