TEMPO: a stochastic benchmarking protocol for evaluating temporal robustness in spiking neural networks
Spiking neural networks are set apart from conventional architectures by their leaky-integrator dynamics and temporal memory, yet the benchmarks most often used to evaluate them do not exercise these properties. In datasets such as N-MNIST and DVS-Gesture the discriminative information lies in spati...
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| Hoofdauteurs: | , |
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| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
IOP Publishing
2026-01-01
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| Reeks: | Neuromorphic Computing and Engineering |
| Onderwerpen: | |
| Online toegang: | https://doi.org/10.1088/2634-4386/ae84f7 |
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