| A Bayesian Monte Carlo approach for predicting the spread of infectious diseases O Stojanović, J Leugering, G Pipa, S Ghozzi, A Ullrich PloS one 14 (12), e0225838, 2019 | 32 | 2019 |
| The neocortex W Singer, TJ Sejnowski, P Rakic MIT Press, 2019 | 13 | 2019 |
| A unifying framework of synaptic and intrinsic plasticity in neural populations J Leugering, G Pipa Neural computation 30 (4), 945-986, 2018 | 13 | 2018 |
| Neuromorphic computation in multi-delay coupled models P Nieters, J Leugering, G Pipa IBM Journal of Research and Development 61 (2/3), 8: 7-8: 9, 2017 | 12 | 2017 |
| Dendritic plateau potentials can process spike sequences across multiple time-scales J Leugering, P Nieters, G Pipa | 8 | 2023 |
| A minimal model of neural computation with dendritic plateau potentials J Leugering, P Nieters, G Pipa bioRxiv, 2021 | 2 | 2021 |
| Leveraging deep neural networks for lucid dream communication via two-dimensional electrooculography V Amo, N Godt, J Leugering, K Appel PsyArXiv, 2023 | 1 | 2023 |
| Tools and Methodologies for Edge-AI Mixed-Signal Inference Accelerators L Mateu, J Leugering, R Müller, Y Patil, M Mallah, M Breiling, F Pscheidl Embedded Artificial Intelligence, 25-34, 2023 | 1 | 2023 |
| Modeling and analyzing neuromorphic SNNs as discrete event systems J Leugering Proceedings of the 2022 Annual Neuro-Inspired Computational Elements …, 2022 | 1 | 2022 |
| Bayesian hierarchical models can infer interpretable predictions of leaf area index from heterogeneous datasets O Stojanović, B Siegmann, T Jarmer, G Pipa, J Leugering Frontiers in Environmental Science 9, 780814, 2022 | 1 | 2022 |
| SEC-Learn: Sensor Edge Cloud for Federated Learning. P Aichroth, C Antes, P Gembatzka, H Graf, D Johnson, M Jung, T Kämpfe, ... Special Session on Next Generation Computing at International Conference on …, 2021 | 1 | 2021 |
| Making spiking neurons more succinct with multi-compartment models J Leugering Proceedings of the 2020 Annual Neuro-Inspired Computational Elements …, 2020 | 1 | 2020 |
| DeepRain–Improved local-scale prediction of precipitation through deep learning. M Schultz, F Kleinert, L Leufen, J Ahring, S Theis, J Keller, G Pipa, ... Geophysical Research Abstracts 21, 2019 | 1 | 2019 |
| Bistable Perception in Conceptor Networks F Meyer zu Driehausen, R Busche, J Leugering, G Pipa Artificial Neural Networks and Machine Learning–ICANN 2019: Workshop and …, 2019 | 1 | 2019 |
| Traumschreiber': measuring and manipulating human sleep with a portable high-quality but low-cost polysomnographic system K Appel, J Leugering, G Pipa Journal of Sleep Research, 2016 | 1 | 2016 |
| TickTockTokens: a minimal building block for event-driven systems J Leugering 2024 Neuro Inspired Computational Elements Conference (NICE), 1-8, 2024 | | 2024 |
| Towards Chip-in-the-loop Spiking Neural Network Training via Metropolis-Hastings Sampling A Safa, V Jaltare, S Sebt, K Gano, J Leugering, G Gielen, ... 2024 Neuro Inspired Computational Elements Conference (NICE), 1-5, 2024 | | 2024 |
| Energy-efficiency Limits on Training AI Systems using Learning-in-Memory Z Chen, J Leugering, G Cauwenberghs, S Chakrabartty arXiv preprint arXiv:2402.14878, 2024 | | 2024 |
| Semiconductor device system F Pscheidl, J Leugering US Patent App. 18/230,543, 2024 | | 2024 |
| Semiconductor device system F Pscheidl, J Leugering | | 2024 |
Gordon PipaProfessor for neuroinformatics - Osnabrueck UniversityVerified email at uos.de
