: Researchers found that using Spiking Neural Networks (SNNs) for this task can reduce inference time by more than an order of magnitude while maintaining or surpassing the accuracy of classical algorithms.

: In Positron Emission Tomography (PET), matching pairs of photons (coincidences) is computationally expensive at high rates.

: It is widely used to prove the existence of solutions for nonlinear differential equations and boundary value problems.

kitheory_coincidence

Kitheory_coincidence

: Researchers found that using Spiking Neural Networks (SNNs) for this task can reduce inference time by more than an order of magnitude while maintaining or surpassing the accuracy of classical algorithms.

: In Positron Emission Tomography (PET), matching pairs of photons (coincidences) is computationally expensive at high rates. kitheory_coincidence

: It is widely used to prove the existence of solutions for nonlinear differential equations and boundary value problems. : Researchers found that using Spiking Neural Networks

kitheory_coincidence

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