Binary Tuning is Optimal for Neural Rate Coding with High Temporal Resolution. - Matthias Bethge; David Rotermund; Klaus Pawelzik (NIPS, 2002)

Optimal Short-Term Population Coding: When Fisher Information Fails. - Matthias Bethge; David Rotermund; Klaus Pawelzik (Neural Comput., 2002)

An Algorithm for Fast Pattern Recognition with Random Spikes. - Udo A. Ernst; David Rotermund; Klaus Pawelzik (DAGM-Symposium, 2004)

On-line adaptation of neuro-prostheses with neuronal evaluation signals. - Klaus Pawelzik; Udo A. Ernst; David Rotermund (ESANN, 2006)

Towards On-line Adaptation of Neuro-prostheses with Neuronal Evaluation Signals. - David Rotermund; Udo A. Ernst; Klaus R. Pawelzik (Biol. Cybern., 2006)

Efficient Computation Based on Stochastic Spikes. - Udo Ernst; David Rotermund; Klaus Pawelzik (Neural Comput., 2007)

Extraction of information from the dynamical activities of neural networks. - David Rotermund (2007)

Development of a fully implantable recording system for ECoG signals. - Jonas Pistor; Janpeter Hoeffmann; David Rotermund; Elena Tolstosheeva; Tim Schellenberg; Dmitriy Boll; Víctor Gordillo-González; Sunita Mandon; Dagmar Peters-Drolshagen; Andreas K. Kreiter; Martin Schneider 004; Walter Lang; et al. (DATE, 2013)

Implications for a Wireless, External Device System to Study Electrocorticography. - David Rotermund; Jonas Pistor; Janpeter Hoeffmann; Tim Schellenberg; Dmitriy Boll; Elena Tolstosheeva; Dieter Gauck; Heiko Stemmann; Dagmar Peters-Drolshagen; Andreas K. Kreiter; Martin Schneider 004; Steffen Paul; et al. (Sensors, 2017)

Back-Propagation Learning in Deep Spike-By-Spike Networks. - David Rotermund; Klaus R. Pawelzik (Frontiers Comput. Neurosci., 2019)

Accelerator Framework of Spike-By-Spike Neural Networks for Inference and Incremental Learning in Embedded Systems. - Yarib Nevarez; Alberto García Ortiz; David Rotermund; Klaus R. Pawelzik (MOCAST, 2020)

Accelerating Spike-by-Spike Neural Networks on FPGA With Hybrid Custom Floating-Point and Logarithmic Dot-Product Approximation. - Yarib Nevarez; David Rotermund; Klaus R. Pawelzik; Alberto García Ortiz (IEEE Access, 2021)

Empirical Analysis of Full-System Approximation on Non-Spiking and Spiking Neural Networks. - Amir Najafi 001; David Rotermund; Ardalan Najafi; Klaus R. Pawelzik; Alberto García Ortiz (MOCAST, 2023)

Including local feature interactions in deep non-negative matrix factorization networks improves performance. - Mahbod Nouri; David Rotermund; Alberto García Ortiz; Klaus R. Pawelzik (CoRR, 2025)