Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Advancing Residual Learning towards Powerful Deep Spiking Neural
  Networks   Despite the rapid progress of neuromorphic computing, inadequate capacity and
insufficient representation power of spiking neural networks (SNNs) severely
restrict their application scope in practice. Residual learning and shortcuts
have been evidenced as an important approach for training deep neural networks,
but rarely did previous work assess their applicability to the characteristics
of spike-based communication and spatiotemporal dynamics. In this paper, we
first identify that this negligence leads to impeded information flow and
accompanying degradation problem in previous residual SNNs. Then we propose a
novel SNN-oriented residual block, MS-ResNet, which is able to significantly
extend the depth of directly trained SNNs, e.g. up to 482 layers on CIFAR-10
and 104 layers on ImageNet, without observing any slight degradation problem.
We validate the effectiveness of MS-ResNet on both frame-based and neuromorphic
datasets, and MS-ResNet104 achieves a superior result of 76.02% accuracy on
ImageNet, the first time in the domain of directly trained SNNs. Great energy
efficiency is also observed that on average only one spike per neuron is needed
to classify an input sample. We believe our powerful and scalable models will
provide a strong support for further exploration of SNNs.

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The categories of this paper are: hep-th
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The categories of this paper are: patt-sol
15
The categories of this paper are: nucl-ex
14
The categories of this paper are: math-ph
18
The categories of this paper are: econ
3
The categories of this paper are: physics
33
The categories of this paper are: plasm-ph
17
The categories of this paper are: q-fin
12
The categories of this paper are: nucl-th
16
The categories of this paper are: stat
37
The categories of this paper are: supr-con
13
The categories of this paper are: quant-ph
23
The categories of this paper are: solv-int
34
The categories of this paper are: chem-ph
31
The categories of this paper are: ao-sci
6
The categories of this paper are: astro-ph