Deep residual learning in spiking neural networks
Abstract Deep Spiking Neural Networks (SNNs) present optimization difficulties for gradient-
based approaches due to discrete binary activation and complex spatial-temporal dynamics …
based approaches due to discrete binary activation and complex spatial-temporal dynamics …
Deep Residual Learning in Spiking Neural Networks
W Fang, Z Yu, Y Chen, T Huang… - Advances in Neural …, 2021 - openreview.net
Deep Spiking Neural Networks (SNNs) present optimization difficulties for gradient-based
approaches due to discrete binary activation and complex spatial-temporal dynamics …
approaches due to discrete binary activation and complex spatial-temporal dynamics …
Deep Residual Learning in Spiking Neural Networks
W Fang, Z Yu, Y Chen, T Huang, T Masquelier… - arXiv preprint arXiv …, 2021 - arxiv.org
Deep Spiking Neural Networks (SNNs) present optimization difficulties for gradient-based
approaches due to discrete binary activation and complex spatial-temporal dynamics …
approaches due to discrete binary activation and complex spatial-temporal dynamics …
[PDF][PDF] Deep Residual Learning in Spiking Neural Networks
W Fang, Z Yu, Y Chen, T Huang… - arXiv preprint arXiv …, 2021 - researchgate.net
Abstract Deep Spiking Neural Networks (SNNs) present optimization difficulties for gradient-
based approaches due to discrete binary activation and complex spatialtemporal dynamics …
based approaches due to discrete binary activation and complex spatialtemporal dynamics …
[PDF][PDF] Deep Residual Learning in Spiking Neural Networks
W Fang, Z Yu, Y Chen, T Huang, T Masquelier, Y Tian - yuzhaofei.github.io
Abstract Deep Spiking Neural Networks (SNNs) present optimization difficulties for gradient-
based approaches due to discrete binary activation and complex spatialtemporal dynamics …
based approaches due to discrete binary activation and complex spatialtemporal dynamics …
Deep Residual Learning in Spiking Neural Networks
W Fang, Z Yu, Y Chen, T Huang, T Masquelier… - arXiv e …, 2021 - ui.adsabs.harvard.edu
Abstract Deep Spiking Neural Networks (SNNs) present optimization difficulties for gradient-
based approaches due to discrete binary activation and complex spatial-temporal dynamics …
based approaches due to discrete binary activation and complex spatial-temporal dynamics …
Deep Residual Learning in Spiking Neural Networks
W Fang, Z Yu, Y Chen, T Huang… - Advances in Neural …, 2021 - proceedings.neurips.cc
Abstract Deep Spiking Neural Networks (SNNs) present optimization difficulties for gradient-
based approaches due to discrete binary activation and complex spatial-temporal dynamics …
based approaches due to discrete binary activation and complex spatial-temporal dynamics …
Deep Residual Learning in Spiking Neural Networks
W Fang, Z Yu, Y Chen, T Huang, T Masquelier, Y Tian - NeurIPS 2021, 2021 - hal.science
Deep Spiking Neural Networks (SNNs) present optimization difficulties for gradient-based
approaches due to discrete binary activation and complex spatial-temporal dynamics …
approaches due to discrete binary activation and complex spatial-temporal dynamics …
[PDF][PDF] Deep Residual Learning in Spiking Neural Networks
W Fang, Z Yu, Y Chen, T Huang, T Masquelier, Y Tian - openreview.net
Abstract Deep Spiking Neural Networks (SNNs) present optimization difficulties for gradient-
based approaches due to discrete binary activation and complex spatialtemporal dynamics …
based approaches due to discrete binary activation and complex spatialtemporal dynamics …
[PDF][PDF] Deep Residual Learning in Spiking Neural Networks
W Fang, Z Yu, Y Chen, T Huang, T Masquelier, Y Tian - researchgate.net
Abstract Deep Spiking Neural Networks (SNNs) present optimization difficulties for gradient-
based approaches due to discrete binary activation and complex spatialtemporal dynamics …
based approaches due to discrete binary activation and complex spatialtemporal dynamics …