activity
20192022
most citedTemporal Efficient Training of Spiking Neural Network via Gradient Re-weighting

103 citations · 159 across the 8 of their papers we have counts for

collaborators

11 papers

cs.AI20221 cited

Exploring Temporal Information Dynamics in Spiking Neural Networks

Youngeun Kim, Yuhang Li, Hyoungseob Park +3

Most existing Spiking Neural Network (SNN) works state that SNNs may utilize temporal information dynamics of spikes. However, an explicit analysis of temporal information dynamics…

cs.NE20227 cited

Wearable-based Human Activity Recognition with Spatio-Temporal Spiking Neural Networks

Yuhang Li, Ruokai Yin, Hyoungseob Park +2

We study the Human Activity Recognition (HAR) task, which predicts user daily activity based on time series data from wearable sensors. Recently, researchers use end-to-end Artific…

cs.CV20226 cited

AnimeRun: 2D Animation Visual Correspondence from Open Source 3D Movies

Li Siyao, Yuhang Li, Bo Li +3

Existing correspondence datasets for two-dimensional (2D) cartoon suffer from simple frame composition and monotonic movements, making them insufficient to simulate real animations…

cs.NE202213 cited

Converting Artificial Neural Networks to Spiking Neural Networks via Parameter Calibration

Yuhang Li, Shikuang Deng, Xin Dong +1

Spiking Neural Network (SNN), originating from the neural behavior in biology, has been recognized as one of the next-generation neural networks. Conventionally, SNNs can be obtain…

cs.LG20225 cited

Addressing Client Drift in Federated Continual Learning with Adaptive Optimization

Yeshwanth Venkatesha, Youngeun Kim, Hyoungseob Park +2

Federated learning has been extensively studied and is the prevalent method for privacy-preserving distributed learning in edge devices. Correspondingly, continual learning is an e…

cs.NE2022103 cited

Temporal Efficient Training of Spiking Neural Network via Gradient Re-weighting

Shikuang Deng, Yuhang Li, Shanghang Zhang +1

Recently, brain-inspired spiking neuron networks (SNNs) have attracted widespread research interest because of their event-driven and energy-efficient characteristics. Still, it is…