| Demonstrating advantages of neuromorphic computation: a pilot study T Wunderlich, AF Kungl, E Müller, A Hartel, Y Stradmann, SA Aamir, ... Frontiers in neuroscience 13, 260, 2019 | 101 | 2019 |
| Porting HTM models to the Heidelberg neuromorphic computing platform S Billaudelle, S Ahmad arXiv preprint arXiv:1505.02142, 2015 | 47 | 2015 |
| Fast and energy-efficient neuromorphic deep learning with first-spike times J Göltz, L Kriener, A Baumbach, S Billaudelle, O Breitwieser, B Cramer, ... Nature machine intelligence 3 (9), 823-835, 2021 | 45 | 2021 |
| Versatile emulation of spiking neural networks on an accelerated neuromorphic substrate S Billaudelle, Y Stradmann, K Schreiber, B Cramer, A Baumbach, D Dold, ... 2020 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2020 | 44 | 2020 |
| Fast and deep neuromorphic learning with first-spike coding J Göltz, A Baumbach, S Billaudelle, AF Kungl, O Breitwieser, K Meier, ... Proceedings of the neuro-inspired computational elements workshop, 1-3, 2020 | 43 | 2020 |
| Surrogate gradients for analog neuromorphic computing B Cramer, S Billaudelle, S Kanya, A Leibfried, A Grübl, V Karasenko, ... Proceedings of the National Academy of Sciences 119 (4), e2109194119, 2022 | 31 | 2022 |
| The BrainScaleS-2 accelerated neuromorphic system with hybrid plasticity C Pehle, S Billaudelle, B Cramer, J Kaiser, K Schreiber, Y Stradmann, ... Frontiers in Neuroscience 16, 2022 | 26 | 2022 |
| Verification and design methods for the brainscales neuromorphic hardware system A Grübl, S Billaudelle, B Cramer, V Karasenko, J Schemmel Journal of Signal Processing Systems 92, 1277-1292, 2020 | 26 | 2020 |
| Accelerated analog neuromorphic computing J Schemmel, S Billaudelle, P Dauer, J Weis Analog Circuits for Machine Learning, Current/Voltage/Temperature Sensors …, 2021 | 24 | 2021 |
| Structural plasticity on an accelerated analog neuromorphic hardware system S Billaudelle, B Cramer, MA Petrovici, K Schreiber, D Kappel, ... Neural networks 133, 11-20, 2021 | 21 | 2021 |
| hxtorch: PyTorch for BrainScaleS-2: Perceptrons on Analog Neuromorphic Hardware P Spilger, E Müller, A Emmel, A Leibfried, C Mauch, C Pehle, J Weis, ... IoT Streams for Data-Driven Predictive Maintenance and IoT, Edge, and Mobile …, 2020 | 19 | 2020 |
| Training spiking multi-layer networks with surrogate gradients on an analog neuromorphic substrate B Cramer, S Billaudelle, S Kanya, A Leibfried, A Grübl, V Karasenko, ... arXiv preprint arXiv:2006.07239, 2020 | 17 | 2020 |
| The operating system of the neuromorphic BrainScaleS-1 system E Müller, S Schmitt, C Mauch, S Billaudelle, A Grübl, M Güttler, ... Neurocomputing 501, 790-810, 2022 | 15 | 2022 |
| Emulating dendritic computing paradigms on analog neuromorphic hardware J Kaiser, S Billaudelle, E Müller, C Tetzlaff, J Schemmel, S Schmitt Neuroscience 489, 290-300, 2022 | 15 | 2022 |
| Publishing statistical models: Getting the most out of particle physics experiments K Cranmer, S Kraml, H Prosper, P Bechtle, F Bernlochner, IM Bloch, ... SciPost Physics 12 (1), 037, 2022 | 15 | 2022 |
| Inference with artificial neural networks on analog neuromorphic hardware J Weis, P Spilger, S Billaudelle, Y Stradmann, A Emmel, E Müller, ... IoT Streams for Data-Driven Predictive Maintenance and IoT, Edge, and Mobile …, 2020 | 14 | 2020 |
| Spiking neuromorphic chip learns entangled quantum states S Czischek, A Baumbach, S Billaudelle, B Cramer, L Kades, ... SciPost Physics 12 (1), 039, 2022 | 11 | 2022 |
| Design and implementation of a short term plasticity circuit for a 65 nm neuromorphic hardware system S Billaudelle Masterarbeit, Universität Heidelberg, 2017 | 8 | 2017 |
| A scalable approach to modeling on accelerated neuromorphic hardware E Müller, E Arnold, O Breitwieser, M Czierlinski, A Emmel, J Kaiser, ... Frontiers in neuroscience 16, 2022 | 6 | 2022 |
| Accelerated analog neuromorphic computing. arXiv [Preprint](2020) J Schemmel, S Billaudelle, P Dauer, J Weis arXiv preprint arXiv:2003.11996 12, 2003 | 6 | 2003 |
