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20242026
most citedAdaptive Reorganization of Neural Pathways for Continual Learning with Spiking Neural Networks

2 citations · 2 across the 1 of their papers we have counts for

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6 papers

cs.NE20262 cited

Adaptive Reorganization of Neural Pathways for Continual Learning with Spiking Neural Networks

Bing Han, Feifei Zhao, Wenxuan Pan +4

The human brain can self-organize rich and diverse sparse neural pathways to incrementally master hundreds of cognitive tasks. However, most existing continual learning algorithms…

cs.AI2025

Brain-inspired and Self-based Artificial Intelligence

Yi Zeng, Feifei Zhao, Yuxuan Zhao +17

The question "Can machines think?" and the Turing Test to assess whether machines could achieve human-level intelligence is one of the roots of AI. With the philosophical argument…

cs.NE2025

Incorporating brain-inspired mechanisms for multimodal learning in artificial intelligence

Xiang He, Dongcheng Zhao, Yang Li +3

Multimodal learning enhances the perceptual capabilities of cognitive systems by integrating information from different sensory modalities. However, existing multimodal fusion rese…

cs.NE2024

Similarity-based context aware continual learning for spiking neural networks

Bing Han, Feifei Zhao, Yang Li +3

Biological brains have the capability to adaptively coordinate relevant neuronal populations based on the task context to learn continuously changing tasks in real-world environmen…

cs.CV2024

CACE-Net: Co-guidance Attention and Contrastive Enhancement for Effective Audio-Visual Event Localization

Xiang He, Xiangxi Liu, Yang Li +5

The audio-visual event localization task requires identifying concurrent visual and auditory events from unconstrained videos within a network model, locating them, and classifying…

cs.NE2024

Spiking Neural Networks with Consistent Mapping Relations Allow High-Accuracy Inference

Yang Li, Xiang He, Qingqun Kong +1

Spike-based neuromorphic hardware has demonstrated substantial potential in low energy consumption and efficient inference. However, the direct training of deep spiking neural netw…