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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,742 papers · 148 categories

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0111 · Dec 201919922001200920172026
2 results for “time-to-first-spike”
T2FSNN: Deep Spiking Neural Networks with Time-to-first-spike Codingcs.NE

T2FSNN improves deep SNNs by reducing spikes and latency.

problem Inefficiency in spiking neural networks due to lack of scalable training algorithms.
method Introduces time-to-first-spike coding with kernel-based dynamic threshold and dendrite, combined with gradient-based optimization and early firing methods.
result Reduces inference latency and spike count by 22% and less than 1% compared to burst coding.
spiking neural networksdeep learningenergy efficiencytime-to-first-spikeinference latency
2020-03-26abs ↗pdf ↗
Fast and energy-efficient neuromorphic deep learning with first-spike timescs.NE

A learning rule for first-spike times in neural networks reduces energy consumption and reaction times.

problem Energy efficiency and reaction time in neuromorphic systems.
method Derivation of a learning rule for first-spike times in leaky integrate-and-fire neurons, using only input and output spike times.
result Demonstrated that the approach can implement error backpropagation in hierarchical spiking networks and is capable of harnessing neuromorphic system's speed and energy characteristics.
neuromorphic learningfirst-spike timesenergy efficiencyreaction timeerror backpropagation
2019-12-24abs ↗pdf ↗