| Surrogate gradient learning in spiking neural networks: Bringing the power of gradient-based optimization to spiking neural networks EO Neftci, H Mostafa, F Zenke IEEE Signal Processing Magazine 36 (6), 51-63, 2019 | 688 | 2019 |
| 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 | 615 | 2015 |
| Supervised learning based on temporal coding in spiking neural networks H Mostafa IEEE transactions on neural networks and learning systems 29 (7), 3227-3235, 2017 | 348 | 2017 |
| 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 | 256 | 2018 |
| Parameter efficient training of deep convolutional neural networks by dynamic sparse reparameterization H Mostafa, X Wang International Conference on Machine Learning, 4646--4655, 2019 | 245 | 2019 |
| Synaptic plasticity dynamics for deep continuous local learning (DECOLLE) J Kaiser, H Mostafa, E Neftci Frontiers in Neuroscience 14, 424, 2020 | 188 | 2020 |
| Memristor for computing: Myth or reality? S Hamdioui, S Kvatinsky, G Cauwenberghs, L Xie, N Wald, S Joshi, ... Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017 …, 2017 | 119 | 2017 |
| Deep supervised learning using local errors H Mostafa, V Ramesh, G Cauwenberghs Frontiers in neuroscience 12, 608, 2018 | 103 | 2018 |
| An event-based architecture for solving constraint satisfaction problems H Mostafa, LK Müller, G Indiveri Nature communications 6 (1), 8941, 2015 | 49 | 2015 |
| Implementation of a spike-based perceptron learning rule using TiO2−x memristors H Mostafa, A Khiat, A Serb, CG Mayr, G Indiveri, T Prodromakis Frontiers in neuroscience 9, 357, 2015 | 48 | 2015 |
| Fast classification using sparsely active spiking networks H Mostafa, BU Pedroni, S Sheik, G Cauwenberghs 2017 IEEE International Symposium on Circuits and Systems (ISCAS), 1-4, 2017 | 47 | 2017 |
| Spike-driven threshold-based learning with memristive synapses and neuromorphic silicon neurons E Covi, R George, J Frascaroli, S Brivio, C Mayr, H Mostafa, G Indiveri, ... Journal of Physics D: Applied Physics 51 (34), 344003, 2018 | 28 | 2018 |
| Synaptic plasticity dynamics for deep continuous local learning J Kaiser, H Mostafa, E Neftci arXiv preprint arXiv:1811.10766, 2018 | 25 | 2018 |
| Robust federated learning through representation matching and adaptive hyper-parameters H Mostafa arXiv preprint arXiv:1912.13075, 2019 | 22 | 2019 |
| Beyond spike-timing dependent plasticity in memristor crossbar arrays H Mostafa, C Mayr, G Indiveri 2016 IEEE International Symposium on Circuits and Systems (ISCAS), 926-929, 2016 | 19 | 2016 |
| Rhythmic inhibition allows neural networks to search for maximally consistent states H Mostafa, LK Müller, G Indiveri Neural computation 27 (12), 2510-2547, 2015 | 16 | 2015 |
| A re-configurable on-line learning spiking neuromorphic processor Q Ning, H Mostafa, F Corradi, M Osswald, F Stefanini, D Sumislawska, ... Front. Neurosci 9 (141), 10.3389, 2015 | 16 | 2015 |
| A hybrid analog/digital spike-timing dependent plasticity learning circuit for neuromorphic VLSI multi-neuron architectures H Mostafa, F Corradi, F Stefanini, G Indiveri 2014 IEEE International Symposium on Circuits and Systems (ISCAS), 854-857, 2014 | 16 | 2014 |
| Sequential activity in asymmetrically coupled winner-take-all circuits H Mostafa, G Indiveri Neural computation 26 (9), 1973-2004, 2014 | 13 | 2014 |
| A learning framework for winner-take-all networks with stochastic synapses H Mostafa, G Cauwenberghs Neural computation 30 (6), 1542-1572, 2018 | 12 | 2018 |
