Publications

Janis Keck, Caswell Barry, Christian F. Doeller, and Jürgen Jost. Impact of symmetry in local learning rules on predictive neural representations and generalization in spatial navigation. PLOS Computational Biology, (21)6:1-37, Public Library of Science, June 2025. [PUMA: neural predictive representations xack yaff] URL

Oliver Kirsten, Martin Bogdan, and Sophie Adama. Evaluating the DoC-Forest tool for Classifying the State of Consciousness in a Completely Locked-In Syndrome Patient. 2023 7th International Conference on Imaging, Signal Processing and Communications (ICISPC), 37-41, 2023. [PUMA: Complexity Computational Consciousness Information Locked-In Measures Modeling Neuroscience Prediction Predictive Processing Signal Syndrome Theory Training algorithms and data learning modeling models processing zno machine]

Claudio Hartmann, Martin Hahmann, Wolfgang Lehner, and Frank Rosenthal. Exploiting big data in time series forecasting: A cross-sectional approach. 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA), 1--10, 2015. [PUMA: Big Data Forecasting History Mathematical Predictive Time analysis data model models series zno]

Scarlet Brockmoeller, Amelie Echle, Narmin Ghaffari Laleh, Susanne Eiholm, Marie Louise Malmstrøm, Tine Plato Kuhlmann, Katarina Levic, Heike Irmgard Grabsch, Nicholas P West, Oliver Lester Saldanha, Katerina Kouvidi, Aurora Bono, Lara R Heij, Titus J Brinker, Ismayil Gögenür, Philip Quirke, and Jakob Nikolas Kather. Deep learning identifies inflamed fat as a risk factor for lymph node metastasis in early colorectal cancer. J. Pathol., (256)3:269--281, Wiley, March 2022. [PUMA: AI; LNM adipose and artificial bowel colorectal deep digital early inflamed metastasis; new pT1 pT2 prediction predictive tissue; topic_lifescience zno learning intelligence pathology biomarker cancer]