14 citations · 18 across the 5 of their papers we have counts for
5 papers
Joint sparse coding and temporal dynamics support context reconfiguration
Qianqian Shi, Yue Che, Faqiang Liu +6
Adaptive behavior requires the brain to transition between distinct contexts while maintaining representations of prior experience. The ability to reconfigure neural representation…
Unveiling the Potential of Spiking Dynamics in Graph Representation Learning through Spatial-Temporal Normalization and Coding Strategies
Mingkun Xu, Huifeng Yin, Yujie Wu +5
In recent years, spiking neural networks (SNNs) have attracted substantial interest due to their potential to replicate the energy-efficient and event-driven processing of biologic…
Exploiting Spiking Dynamics with Spatial-temporal Feature Normalization in Graph Learning
Mingkun Xu, Yujie Wu, Lei Deng +3
Biological spiking neurons with intrinsic dynamics underlie the powerful representation and learning capabilities of the brain for processing multimodal information in complex envi…
Towards Both Accurate and Robust Neural Networks without Extra Data
Faqiang Liu, Rong Zhao
Deep neural networks have achieved remarkable performance in various applications but are extremely vulnerable to adversarial perturbation. The most representative and promising me…
Adversarial symmetric GANs: bridging adversarial samples and adversarial networks
Faqiang Liu, Mingkun Xu, Guoqi Li +3
Generative adversarial networks have achieved remarkable performance on various tasks but suffer from training instability. Despite many training strategies proposed to improve tra…