16 citations · 32 across the 9 of their papers we have counts for
9 papers
DSPE: An Energy-Efficient Edge Processor for DeepSeek Inference with MerkleTree-based Incremental Pruning, Multi-Stage Boothing Lookup and Dynamic Adaptive Posit Processing
Yuhan Zhang, Zhou Wang, Zhou Shu +8
In recent years, DeepSeek has achieved strong inference performance but remains hard to deploy on energy-constrained edge devices. This paper presents the DeepSeek Processing Eleme…
ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks
Yufei Guo, Yuhan Zhang, Zhou Jie +5
The Spiking Neural Network (SNN), a biologically inspired neural network infrastructure, has garnered significant attention recently. SNNs utilize binary spike activations for effi…
Spiking Transformer:Introducing Accurate Addition-Only Spiking Self-Attention for Transformer
Yufei Guo, Xiaode Liu, Yuanpei Chen +3
Transformers have demonstrated outstanding performance across a wide range of tasks, owing to their self-attention mechanism, but they are highly energy-consuming. Spiking Neural N…
Technique Report of CVPR 2024 PBDL Challenges
Ying Fu, Yu Li, Shaodi You +96
The intersection of physics-based vision and deep learning presents an exciting frontier for advancing computer vision technologies. By leveraging the principles of physics to info…
Take A Shortcut Back: Mitigating the Gradient Vanishing for Training Spiking Neural Networks
Yufei Guo, Yuanpei Chen, Zecheng Hao +5
The Spiking Neural Network (SNN) is a biologically inspired neural network infrastructure that has recently garnered significant attention. It utilizes binary spike activations to…
Ternary Spike: Learning Ternary Spikes for Spiking Neural Networks
Yufei Guo, Yuanpei Chen, Xiaode Liu +4
The Spiking Neural Network (SNN), as one of the biologically inspired neural network infrastructures, has drawn increasing attention recently. It adopts binary spike activations to…
Spiking PointNet: Spiking Neural Networks for Point Clouds
Dayong Ren, Zhe Ma, Yuanpei Chen +4
Recently, Spiking Neural Networks (SNNs), enjoying extreme energy efficiency, have drawn much research attention on 2D visual recognition and shown gradually increasing application…
Membrane Potential Batch Normalization for Spiking Neural Networks
Yufei Guo, Yuhan Zhang, Yuanpei Chen +5
As one of the energy-efficient alternatives of conventional neural networks (CNNs), spiking neural networks (SNNs) have gained more and more interest recently. To train the deep mo…
RMP-Loss: Regularizing Membrane Potential Distribution for Spiking Neural Networks
Yufei Guo, Xiaode Liu, Yuanpei Chen +5
Spiking Neural Networks (SNNs) as one of the biology-inspired models have received much attention recently. It can significantly reduce energy consumption since they quantize the r…