| A reconfigurable on-line learning spiking neuromorphic processor comprising 256 neurons and 128K synapses N Qiao, H Mostafa, F Corradi, M Osswald, F Stefanini, D Sumislawska, ... Frontiers in neuroscience 9, 141, 2015 | 583 | 2015 |
| NullHop: A flexible convolutional neural network accelerator based on sparse representations of feature maps A Aimar, H Mostafa, E Calabrese, A Rios-Navarro, R Tapiador-Morales, ... IEEE transactions on neural networks and learning systems 30 (3), 644-656, 2018 | 229 | 2018 |
| Neuromorphic architectures for spiking deep neural networks G Indiveri, F Corradi, N Qiao 2015 IEEE International Electron Devices Meeting (IEDM), 4.2. 1-4.2. 4, 2015 | 151 | 2015 |
| Steering a predator robot using a mixed frame/event-driven convolutional neural network DP Moeys, F Corradi, E Kerr, P Vance, G Das, D Neil, D Kerr, T Delbrück 2016 Second international conference on event-based control, communication …, 2016 | 109 | 2016 |
| A neuromorphic event-based neural recording system for smart brain-machine-interfaces F Corradi, G Indiveri IEEE transactions on biomedical circuits and systems 9 (5), 699-709, 2015 | 94 | 2015 |
| A sensitive dynamic and active pixel vision sensor for color or neural imaging applications DP Moeys, F Corradi, C Li, SA Bamford, L Longinotti, FF Voigt, S Berry, ... IEEE transactions on biomedical circuits and systems 12 (1), 123-136, 2017 | 59 | 2017 |
| Live demonstration: Convolutional neural network driven by dynamic vision sensor playing RoShamBo IA Lungu, F Corradi, T Delbrück 2017 IEEE International Symposium on Circuits and Systems (ISCAS), 1-1, 2017 | 55 | 2017 |
| Effective and efficient computation with multiple-timescale spiking recurrent neural networks B Yin, F Corradi, SM Bohté International Conference on Neuromorphic Systems 2020, 1-8, 2020 | 46 | 2020 |
| Dhp19: Dynamic vision sensor 3d human pose dataset E Calabrese, G Taverni, C Awai Easthope, S Skriabine, F Corradi, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 38 | 2019 |
| Accurate and efficient time-domain classification with adaptive spiking recurrent neural networks B Yin, F Corradi, SM Bohté Nature Machine Intelligence 3 (10), 905-913, 2021 | 37 | 2021 |
| Mapping arbitrary mathematical functions and dynamical systems to neuromorphic VLSI circuits for spike-based neural computation F Corradi, C Eliasmith, G Indiveri 2014 IEEE International Symposium on Circuits and Systems (ISCAS), 269-272, 2014 | 36 | 2014 |
| μBrain: An event-driven and fully synthesizable architecture for spiking neural networks J Stuijt, M Sifalakis, A Yousefzadeh, F Corradi Frontiers in neuroscience 15, 538, 2021 | 34 | 2021 |
| ECG-based heartbeat classification in neuromorphic hardware F Corradi, S Pande, J Stuijt, N Qiao, S Schaafsma, G Indiveri, F Catthoor 2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019 | 34 | 2019 |
| Power-accuracy trade-offs for heartbeat classification on neural networks hardware A Balaji, F Corradi, A Das, S Pande, S Schaafsma, F Catthoor Journal of low power electronics 14 (4), 508-519, 2018 | 33 | 2018 |
| Real time unsupervised learning of visual stimuli in neuromorphic VLSI systems M Giulioni, F Corradi, V Dante, P del Giudice Scientific Reports 5 (14730), 2015 | 27 | 2015 |
| Towards a Neuromorphic Vestibular System F Corradi, D Zambrano, M Raglianti, G Passetti, C Laschi, G Indiveri Biomedical Circuits and Systems, IEEE Transactions on, 2014 | 27 | 2014 |
| A spiking implementation of the lamprey's Central Pattern Generator in neuromorphic VLSI E Donati, F Corradi, C Stefanini, G Indiveri 2014 IEEE Biomedical Circuits and Systems Conference (BioCAS) Proceedings …, 2014 | 26 | 2014 |
| A 132 by 104 10μm-Pixel 250μW 1kefps Dynamic Vision Sensor with Pixel-Parallel Noise and Spatial Redundancy Suppression C Li, L Longinotti, F Corradi, T Delbruck 2019 Symposium on VLSI Circuits, C216-C217, 2019 | 24 | 2019 |
| A hybrid analog/digital Spike-Timing Dependent Plasticity learning circuit for neuromorphic VLSI multi-neuron architectures H Mostafa, F Corradi, F Stefanini, G Indiveri Circuits and Systems (ISCAS), 2014 IEEE International Symposium on, 854 - 857, 2014 | 16 | 2014 |
| Wearable monitoring and interpretable machine learning can objectively track progression in patients during cardiac rehabilitation H De Cannière, F Corradi, CJP Smeets, M Schoutteten, C Varon, ... Sensors 20 (12), 3601, 2020 | 15 | 2020 |
Giacomo IndiveriInstitute of Neuroinformatics, University of Zurich and ETH ZurichVerified email at ini.uzh.ch
