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cs.NE2025
Toward Relative Positional Encoding in Spiking Transformers
Changze Lv, Yansen Wang, Dongqi Han +4
Spiking neural networks (SNNs) are bio-inspired networks that mimic how neurons in the brain communicate through discrete spikes, which have great potential in various tasks due to…
cs.NE2024
Advancing Spiking Neural Networks for Sequential Modeling with Central Pattern Generators
Changze Lv, Dongqi Han, Yansen Wang +3
Spiking neural networks (SNNs) represent a promising approach to developing artificial neural networks that are both energy-efficient and biologically plausible. However, applying…
cs.NE2024
Efficient and Effective Time-Series Forecasting with Spiking Neural Networks
Changze Lv, Yansen Wang, Dongqi Han +3
Spiking neural networks (SNNs), inspired by the spiking behavior of biological neurons, provide a unique pathway for capturing the intricacies of temporal data. However, applying S…