Modeling chemical constituents of the atmosphere. - Johann Feichter; Martin G. Schultz; Thomas Diehl (Comput. Sci. Eng., 2002)

Ten years of global burned area products from spaceborne remote sensing - A review: Analysis of user needs and recommendations for future developments. - Florent Mouillot; Martin G. Schultz; Chao Yue; Patricia Cadule; Kevin Tansey; Philippe Ciais; Emilio Chuvieco (Int. J. Appl. Earth Obs. Geoinformation, 2014)

A Web Service Architecture for Objective Station Classification Purposes. - Martin G. Schultz; Sander Apweiler; Jan Vogelsang; Björn Hagemeier; Felix Kleinert; Daniel Mallmann (eScience, 2018)

A New Tool for Automated Quality Control of Environmental Time Series (AutoQC4Env) in Open Web Services. - Najmeh Kaffashzadeh; Felix Kleinert; Martin G. Schultz (BIS (Workshops), 2019)

JUWELS Booster - A Supercomputer for Large-Scale AI Research. - Stefan Kesselheim; Andreas Herten; Kai Krajsek; Jan Ebert; Jenia Jitsev; Mehdi Cherti; Michael Langguth; Bing Gong; Scarlet Stadtler; Amirpasha Mozaffari; Gabriele Cavallaro; Rocco Sedona; et al. (ISC Workshops, 2021)

Context aware benchmarking and tuning of a TByte-scale air quality database and web service. - Clara Betancourt; Björn Hagemeier; Sabine Schröder; Martin G. Schultz (Earth Sci. Informatics, 2021)

HPC-oriented Canonical Workflows for Machine Learning Applications in Climate and Weather Prediction. - Amirpasha Mozaffari; Michael Langguth; Bing Gong; Jessica Ahring; Adrian Rojas Campos; Pascal Nieters; Otoniel José Campos Escobar; Martin Wittenbrink; Peter Baumann 001; Martin G. Schultz (Data Intell., 2022)

Enabling Canonical Analysis Workflows Documented Data Harmonization on Global Air Quality Data. - Sabine Schröder; Eleonora Epp; Amirpasha Mozaffari; Mathilde Romberg; Niklas Selke; Martin G. Schultz (Data Intell., 2022)

Multi-Modal Self-Supervised Learning for Boosting Crop Classification Using Sentinel2 and Planetscope. - Ankit Patnala; Scarlet Stadtler; Martin G. Schultz; Juergen Gall (IGARSS, 2023)

End-to-End Process Orchestration of Earth Observation Data Workflows with Apache Airflow on High Performance Computing. - Liang Tian; Rocco Sedona; Amirpasha Mozaffari; Enxhi Kreshpa; Claudia Paris; Morris Riedel; Martin G. Schultz; Gabriele Cavallaro (IGARSS, 2023)

AtmoRep: A stochastic model of atmosphere dynamics using large scale representation learning. - Christian Lessig; Ilaria Luise; Bing Gong; Michael Langguth; Scarlet Stadtler; Martin G. Schultz (CoRR, 2023)

Generating Views Using Atmospheric Correction for Contrastive Self-Supervised Learning of Multispectral Images. - Ankit Patnala; Scarlet Stadtler; Martin G. Schultz; Juergen Gall (IEEE Geosci. Remote. Sens. Lett., 2023)

Mantik: A Workflow Platform for the Development of Artificial Intelligence on High-Performance Computing Infrastructures. - Thomas Seidler; Fabian Emmerich; Kristian Ehlert; Rico Berner; Oliver Nagel-Kanzler; Norbert Schultz; Markus Quade; Martin G. Schultz; Markus Abel (J. Open Source Softw., 2024)