All software

SeisBench: A toolbox for machine learning in seismology

SeisBench is an open-source Python toolbox for machine learning in seismology. It brings together the whole machine learning model lifecycle: datasets and benchmarks, models and training pipelines, and efficient implementations for deploying the models in production.

CoMOLA

CoMOLA is a python tool for optimal spatial allocation of land uses. The tool creates optimal land-use maps for up to four objectives. It takes into account constraints and can be coupled with external models to evaluate different objectives (e.g. ecosystem services/biodiversity models)

AMIRIS

AMIRIS is the open Agent-based Market model for the Investigation of Renewable and Integrated energy Systems. It aims at enabling scientists to dissect the complex questions arising with respect to future energy markets, their market design, and energy-related policy instruments.

FlexiGIS

FlexiGIS is a software tool for processing and analysing GIS-based data to design urban energy systems. Models developed with FlexiGIS enable the exploration and assessment of flexibility options in cities.

GSTools

GSTools is a Python-based software suite for solving a wide range of geostatistical problems. GSTools provides methods for generating different classes of correlated random fields; it can perform kriging, variogram estimation and much more.

CellDetection

An open-source Python package, offering advanced AI methods for the identification and segmentation of biomedical objects, such as cells, in image data. Includes trained models that work out-of-the-box for a wide range of use cases.

pycomlink

A python toolbox for deriving rainfall information from commercial microwave link (CML) data.

GOLEM

GOLEM is a modelling platform for thermal-hydraulic-mechanical and non-reactive chemical processes in fractured and faulted porous media, based on the MOOSE framework

Allpix Squared

Allpix Squared is a semiconductor detector simulation framework. The goal of the framework is to provide a complete and easy-to-use package for end-to-end simulations of semiconductor detector performance from incident ionizing radiation until the digitization of hits in the detector chip.

ESMValCore

SpatialData framework

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

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.