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cs.NE2026
STEMS: Spatial-Temporal Mapping For Spiking Neural Networks
Sherif Eissa, Sander Stuijk, Floran De Putter +3
Spiking Neural Networks (SNNs) are promising bio-inspired third-generation neural networks. Recent research has trained deep SNN models with accuracy on par with Artificial Neural…
cs.NE2025
Hardware-In-The-Loop Training of a 4f Optical Correlator with Logarithmic Complexity Reduction for CNNs
Lorenzo Pes, Maryam Dehbashizadeh Chehreghan, Rick Luiken +3
This work evaluates a forward-only learning algorithm on the MNIST dataset with hardware-in-the-loop training of a 4f optical correlator, achieving 87.6% accuracy with O(n2) comple…