1 citations · 1 across the 4 of their papers we have counts for
4 papers
Evolving Efficient Genetic Encoding for Deep Spiking Neural Networks
Wenxuan Pan, Feifei Zhao, Bing Han +2
By exploiting discrete signal processing and simulating brain neuron communication, Spiking Neural Networks (SNNs) offer a low-energy alternative to Artificial Neural Networks (ANN…
Brain-inspired Evolutionary Architectures for Spiking Neural Networks
Wenxuan Pan, Feifei Zhao, Zhuoya Zhao +1
The complex and unique neural network topology of the human brain formed through natural evolution enables it to perform multiple cognitive functions simultaneously. Automated evol…
Enhancing Efficient Continual Learning with Dynamic Structure Development of Spiking Neural Networks
Bing Han, Feifei Zhao, Yi Zeng +2
Children possess the ability to learn multiple cognitive tasks sequentially, which is a major challenge toward the long-term goal of artificial general intelligence. Existing conti…
Adaptive structure evolution and biologically plausible synaptic plasticity for recurrent spiking neural networks
Wenxuan Pan, Feifei Zhao, Yi Zeng +1
The architecture design and multi-scale learning principles of the human brain that evolved over hundreds of millions of years are crucial to realizing human-like intelligence. Spi…