Machine Learning on Simulated and Real Farm Data Based on an Ontology-Controlled Data Infrastructure. - Alexander Münzberg; Christian Troost; Daniel Martini; Francisco Mendoza 004; Rajiv Kumar Srivastava; Thomas Berger; Liv Seuring; Nils Reinosch; Thilo Streck; Ansgar Bernardi (AAAI Spring Symposium: MAKE, 2022)

Using Transfer Learning for Quality Improved Forecasting of Temporal Agricultural Processes by Adapting Convolutional Neural Networks. - Alexander Münzberg; Christian Troost; Ansgar Bernardi (GI-Jahrestagung, 2022)

Landwirtschaftliche Ertragsvorhersage im Kontext begrenzter realer Trainingsdatensätze: ein Transfer-Learning-Ansatz unter Verwendung tieferneuronalerNetze. - Alexander Münzberg; Christian Troost; Nils Reinosch; Daniel Martini; Liv Seuring; Alexander Niehus; Rajiv Kumar Srivastava; Thilo Streck; Thomas Berger; Ansgar Bernardi (GI-Jahrestagung, 2023)

SIMLEARN - Ontologiegestützte Integration von Simulationsmodellen, Systemen für maschinelles Lernen und Planungsdaten. - Nils Reinosch; Alexander Münzberg; Daniel Martini; Alexander Niehus; Liv Seuring; Christian Troost; Rajiv Kumar Srivastava; Thomas Berger; Thilo Streck; Ansgar Bernardi (GIL Jahrestagung, 2023)

How to keep it adequate: A protocol for ensuring validity in agent-based simulation. - Christian Troost; Robert Huber; Andrew R. Bell; Hedwig van Delden; Tatiana Filatova; Quang Bao Le; Melvin Lippe; Leila Niamir; J. Gareth Polhill; Zhanli Sun; Thomas Berger (Environ. Model. Softw., 2023)

Towards reusable building blocks for agent-based modelling and theory development. - Uta Berger; Andrew R. Bell; C. Michael Barton; Émile J. L. Chappin; Gunnar Dreßler; Tatiana Filatova; Thibault Fronville; Allen Lee; Emiel van Loon; Iris Lorscheid; Matthias Meyer; Birgit Müller; et al. (Environ. Model. Softw., 2024)