3 papers
cs.NE2026
SpikingGamma: Surrogate-Gradient Free and Temporally Precise Online Training of Spiking Neural Networks with Smoothed Delays
Roel Koopman, Sebastian Otte, Sander Bohté
Neuromorphic hardware implementations of Spiking Neural Networks (SNNs) promise energy-efficient, low-latency AI through sparse, event-driven computation. Yet, training SNNs under…
cs.LG2024
Average-Over-Time Spiking Neural Networks for Uncertainty Estimation in Regression
Tao Sun, Sander Bohté
Uncertainty estimation is a standard tool to quantify the reliability of modern deep learning models, and crucial for many real-world applications. However, efficient uncertainty e…
cs.SD2024
DPSNN: Spiking Neural Network for Low-Latency Streaming Speech Enhancement
Tao Sun, Sander Bohté
Speech enhancement (SE) improves communication in noisy environments, affecting areas such as automatic speech recognition, hearing aids, and telecommunications. With these domains…