13 citations · 18 across the 8 of their papers we have counts for
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cs.NE2026
Controlling the latency in temporal coded spiking models for neuromorphic datasets
Alban Gattepaille, Alexandre Muzy
Exploiting temporal information in datasets with high temporal dependencies (such as spoken keyword recognition) by spiking models is still an open problem. Promising frameworks in…
cs.NE2026
Design and Analysis of Temporal Representations in Neural Networks
Alban Colas-Gattepaille, Alexandre Muzy
The ability to represent temporal information is often hypothesized to underlie the efficiency and learning capabilities of biological neural networks. This motivates the developme…
cs.NE2025
Delay Neural Networks (DeNN) for exploiting temporal information in event-based datasets
Alban Gattepaille, Alexandre Muzy
In Deep Neural Networks (DNN) and Spiking Neural Networks (SNN), the information of a neuron is computed based on the sum of the amplitudes (weights) of the electrical potentials r…