87 citations · 170 across the 23 of their papers we have counts for
9 papers · 1 filter
Rethinking Pairwise Token Interaction in Spiking Transformers
Sicheng Shen, Dongcheng Zhao, Zhiyuan Li +5
Spiking Transformers inherit token interaction mechanisms from conventional Transformers, yet their sparse binary representations fundamentally alter how token-to-token communicati…
Neuro-Vision to Language: Enhancing Brain Recording-based Visual Reconstruction and Language Interaction
Guobin Shen, Dongcheng Zhao, Xiang He +5
Decoding non-invasive brain recordings is pivotal for advancing our understanding of human cognition but faces challenges due to individual differences and complex neural signal re…
FireFly v2: Advancing Hardware Support for High-Performance Spiking Neural Network with a Spatiotemporal FPGA Accelerator
Jindong Li, Guobin Shen, Dongcheng Zhao +2
Spiking Neural Networks (SNNs) are expected to be a promising alternative to Artificial Neural Networks (ANNs) due to their strong biological interpretability and high energy effic…
Artificial to Spiking Neural Networks Conversion for Scientific Machine Learning
Qian Zhang, Chenxi Wu, Adar Kahana +4
We introduce a method to convert Physics-Informed Neural Networks (PINNs), commonly used in scientific machine learning, to Spiking Neural Networks (SNNs), which are expected to ha…
FireFly: A High-Throughput Hardware Accelerator for Spiking Neural Networks with Efficient DSP and Memory Optimization
Jindong Li, Guobin Shen, Dongcheng Zhao +2
Spiking neural networks (SNNs) have been widely used due to their strong biological interpretability and high energy efficiency. With the introduction of the backpropagation algori…
BrainCog: A Spiking Neural Network based Brain-inspired Cognitive Intelligence Engine for Brain-inspired AI and Brain Simulation
Yi Zeng, Dongcheng Zhao, Feifei Zhao +16
Spiking neural networks (SNNs) have attracted extensive attentions in Brain-inspired Artificial Intelligence and computational neuroscience. They can be used to simulate biological…
DPSNN: A Differentially Private Spiking Neural Network with Temporal Enhanced Pooling
Jihang Wang, Dongcheng Zhao, Guobin Shen +2
Privacy protection is a crucial issue in machine learning algorithms, and the current privacy protection is combined with traditional artificial neural networks based on real value…
Spiking Neural Operators for Scientific Machine Learning
Adar Kahana, Qian Zhang, Leonard Gleyzer +1
The main computational task of Scientific Machine Learning (SciML) is function regression, required both for inputs as well as outputs of a simulation. Physics-Informed Neural Netw…
Spiking CapsNet: A Spiking Neural Network With A Biologically Plausible Routing Rule Between Capsules
Dongcheng Zhao, Yang Li, Yi Zeng +2
Spiking neural network (SNN) has attracted much attention due to their powerful spatio-temporal information representation ability. Capsule Neural Network (CapsNet) does well in as…