Backpropagation-Based Learning Techniques for Deep Spiking Neural Networks: A Survey von Dampfhoffer, Manon, Mesquida, Thomas, Valentian, Alexandre, Anghel, Lorena

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Modèles et algorithmes pour l'implémentation de réseaux de neurones impulsionnels à faible consommation énergétique sur du matériel neuromorphique von Dampfhoffer, Manon

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Are SNNs Really More Energy-Efficient Than ANNs? an In-Depth Hardware-Aware Study von Dampfhoffer, Manon, Mesquida, Thomas, Valentian, Alexandre, Anghel, Lorena

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OxRAM + OTS optimization for binarized neural network hardware implementation von Minguet Lopez, J, Hirtzlin, T, Dampfhoffer, M, Grenouillet, L, Reganaz, L, Navarro, G, Carabasse, C, Vianello, E, Magis, T, Deleruyelle, D, Bocquet, M, Portal, J M, Andrieu, F, Molas, G

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Investigating Current-Based and Gating Approaches for Accurate and Energy-Efficient Spiking Recurrent Neural Networks von Dampfhoffer, Manon, Mesquida, Thomas, Valentian, Alexandre, Anghel, Lorena

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1S1R Optimization for High‐Frequency Inference on Binarized Spiking Neural Networks von Minguet Lopez, Joel, Rafhay, Quentin, Dampfhoffer, Manon, Reganaz, Lucas, Castellani, Niccolo, Meli, Valentina, Martin, Simon, Grenouillet, Laurent, Navarro, Gabriele, Magis, Thomas, Carabasse, Catherine, Hirtzlin, Tifenn, Vianello, Elisa, Deleruyelle, Damien, Portal, Jean‐Michel, Molas, Gabriel, Andrieu, François

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