4 citations · 6 across the 8 of their papers we have counts for
4 papers · 1 filter
DS2TA: Denoising Spiking Transformer with Attenuated Spatiotemporal Attention
Boxun Xu, Hejia Geng, Yuxuan Yin +1
Vision Transformers (ViT) are current high-performance models of choice for various vision applications. Recent developments have given rise to biologically inspired spiking transf…
DISTA: Denoising Spiking Transformer with intrinsic plasticity and spatiotemporal attention
Boxun Xu, Hejia Geng, Yuxuan Yin +1
Among the array of neural network architectures, the Vision Transformer (ViT) stands out as a prominent choice, acclaimed for its exceptional expressiveness and consistent high per…
HoSNN: Adversarially-Robust Homeostatic Spiking Neural Networks with Adaptive Firing Thresholds
Hejia Geng, Peng Li
While spiking neural networks (SNNs) offer a promising neurally-inspired model of computation, they are vulnerable to adversarial attacks. We present the first study that draws ins…
Composing Recurrent Spiking Neural Networks using Locally-Recurrent Motifs and Risk-Mitigating Architectural Optimization
Wenrui Zhang, Hejia Geng, Peng Li
In neural circuits, recurrent connectivity plays a crucial role in network function and stability. However, existing recurrent spiking neural networks (RSNNs) are often constructed…