G. Schumann, J. Awick, und J. M. Gómez, "Natural Language Processing using Federated Learning: A Structured Literature Review" in Proc. 2023 IEEE International Conference on Artificial Intelligence, Blockchain, and Internet of Things (AIBThings), 2023.
doi: 10.1109/AIBThings58340.2023.10292481

G. Schumann und J. M. Gómez, "Unsupervised Contradiction Detection using Sentence Transformations" in Proc. 2023 5th International Conference on Natural Language Processing (ICNLP), 2023.
doi: 10.1109/ICNLP58431.2023.00065

J. Awick, G. Schumann, und J. M. Gómez, "Exploring Federated Learning for Data Integration: A Structured Literature Review" in Proc. 2023 International Conference on Big Data, Knowledge and Control Systems Engineering (BdKCSE), 2023.
doi: 10.1109/BdKCSE59280.2023.10339771

G. Schumann, K. Meyer, und J. M. Gomez, "Query-Based Retrieval of German Regulatory Documents for Internal Auditing Purposes" in Proc. 2022 5th International Conference on Data Science and Information Technology (DSIT), 2022.
doi: 10.1109/DSIT55514.2022.9943943

G. Schumann und J. Marx Gómez, "Natural Language Processing in Internal Auditing--a Structured Literature Review."

G. Schumann, F. Kruse, und J. Nonnenmacher, "A Practice-Oriented, Control-Flow-Based Anomaly Detection Approach for Internal Process Audits" in Proc. International Conference on Service-Oriented Computing, 2020.

M. Beykirch, C. Hilmer, G. Schumann, L. Kölpin, C. Wübbe, M. Mönning, G. Yalcin, K. Lang, T. H. Dam, J. Kathmann, und others, Architektur eines dezentralen, prognosebasierten Energiehandelsmodells.

J. Nonnenmacher, F. Kruse, G. Schumann, und J. Marx Gómez, "Using Autoencoders for Data-Driven Analysis in Internal Auditing" in Proc. Proceedings of the 54th Hawaii International Conference on System Sciences, , p. 5748.