4 citations · 11 across the 6 of their papers we have counts for
6 papers
Biologically-Plausible Topology Improved Spiking Actor Network for Efficient Deep Reinforcement Learning
Duzhen Zhang, Qingyu Wang, Tielin Zhang +1
The success of Deep Reinforcement Learning (DRL) is largely attributed to utilizing Artificial Neural Networks (ANNs) as function approximators. Recent advances in neuroscience hav…
Fourier or Wavelet bases as counterpart self-attention in spikformer for efficient visual classification
Qingyu Wang, Duzhen Zhang, Tilelin Zhang +1
Energy-efficient spikformer has been proposed by integrating the biologically plausible spiking neural network (SNN) and artificial Transformer, whereby the Spiking Self-Attention…
Attention-free Spikformer: Mixing Spike Sequences with Simple Linear Transforms
Qingyu Wang, Duzhen Zhang, Tielin Zhang +1
By integrating the self-attention capability and the biological properties of Spiking Neural Networks (SNNs), Spikformer applies the flourishing Transformer architecture to SNNs de…
Complex Dynamic Neurons Improved Spiking Transformer Network for Efficient Automatic Speech Recognition
Minglun Han, Qingyu Wang, Tielin Zhang +3
The spiking neural network (SNN) using leaky-integrated-and-fire (LIF) neurons has been commonly used in automatic speech recognition (ASR) tasks. However, the LIF neuron is still…
Tuning Synaptic Connections instead of Weights by Genetic Algorithm in Spiking Policy Network
Duzhen Zhang, Tielin Zhang, Shuncheng Jia +2
Learning from interaction is the primary way that biological agents acquire knowledge about their environment and themselves. Modern deep reinforcement learning (DRL) explores a co…
Recent Advances and New Frontiers in Spiking Neural Networks
Duzhen Zhang, Shuncheng Jia, Qingyu Wang
In recent years, spiking neural networks (SNNs) have received extensive attention in brain-inspired intelligence due to their rich spatially-temporal dynamics, various encoding met…