All software

Materials Learning Algorithms

MALA (Materials Learning Algorithms) is a data-driven framework to accelerate electronic structure calculations based on machine learning. Its purpose is to construct neural-network surrogate models for bypassing computationally expensive steps in state-of-the-art density functional simulations.

ESMValCore

JEMRIS

JEMRIS is a versatile, open-source, multi-purpose MRI simulator. It is well-suited for research and education.

SpatialData framework

SpatialData is an open and interoperable data framework for ingesting, representing, processing and visualizing spatial omics datasets.

VarFish

VarFish is a user-friendly web application for the quality control, filtering, prioritization, analysis, and user-based annotation of DNA variant data with a focus on rare disease genetics. It is capable of processing variant call files with single or multiple samples. ...

FatSegNet

A fully automated deep learning pipeline for adipose tissue (visceral and subcutaneous) segmentation on abdominal Dixon MRI.

Aviator

Aviator is a web service facilitating easy surveillance of scientific online tools. It currently checks more than 13,000 websites twice a day for availability and saves numerous features (response time, RAM usage security certificates, analytic tools / trackers, etc.) in a FAIR data repository.

Heat

Heat is a flexible and seamless open-source software for high performance data analytics and machine learning. It provides highly optimized algorithms and data structures for tensor computations using CPUs, GPUs and distributed cluster systems on top of MPI.

LiberTEM

LiberTEM is an open source platform for high-throughput distributed processing of large-scale binary data sets and live data streams using a stream-based programming model. The current focus is pixelated scanning transmission electron microscopy (4DSTEM) and scanning electron beam diffraction data.

Album

A Platform for Replicable Science. Album is an open-source tool that simplifies sharing and running scientific workflows. With isolated environments, metadata for easy discovery, and cross-platform support, it ensures replicability. Designed for collaboration, it’s adopted by leading researchers.

Stable-Baselines3

Stable Baselines3 (SB3) is a set of reliable implementations of reinforcement learning algorithms in PyTorch.

pySDC

pySDC is a Python implementation of the spectral deferred correction approach and its flavors, esp. the parallel-in-time extension PFASST. It is intended for rapid prototyping and educational purposes. New ideas can be tested and first toy problems can be easily implemented.