121 citations · 548 across the 26 of their papers we have counts for
13 papers · 1 filter
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…
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…
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…
Exploring Lottery Ticket Hypothesis in Spiking Neural Networks
Youngeun Kim, Yuhang Li, Hyoungseob Park +3
Spiking Neural Networks (SNNs) have recently emerged as a new generation of low-power deep neural networks, which is suitable to be implemented on low-power mobile/edge devices. As…
To image, or not to image: Class-specific diffractive cameras with all-optical erasure of undesired objects
Bijie Bai, Yi Luo, Tianyi Gan +6
Privacy protection is a growing concern in the digital era, with machine vision techniques widely used throughout public and private settings. Existing methods address this growing…
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…
An Optimization-based Algorithm for Non-stationary Kernel Bandits without Prior Knowledge
Kihyuk Hong, Yuhang Li, Ambuj Tewari
We propose an algorithm for non-stationary kernel bandits that does not require prior knowledge of the degree of non-stationarity. The algorithm follows randomized strategies obtai…
Analysis of Diffractive Neural Networks for Seeing Through Random Diffusers
Yuhang Li, Yi Luo, Bijie Bai +1
Imaging through diffusive media is a challenging problem, where the existing solutions heavily rely on digital computers to reconstruct distorted images. We provide a detailed anal…
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…
Neuromorphic Data Augmentation for Training Spiking Neural Networks
Yuhang Li, Youngeun Kim, Hyoungseob Park +2
Developing neuromorphic intelligence on event-based datasets with Spiking Neural Networks (SNNs) has recently attracted much research attention. However, the limited size of event-…
QDrop: Randomly Dropping Quantization for Extremely Low-bit Post-Training Quantization
Xiuying Wei, Ruihao Gong, Yuhang Li +2
Recently, post-training quantization (PTQ) has driven much attention to produce efficient neural networks without long-time retraining. Despite its low cost, current PTQ works tend…
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…
Neural Architecture Search for Spiking Neural Networks
Youngeun Kim, Yuhang Li, Hyoungseob Park +2
Spiking Neural Networks (SNNs) have gained huge attention as a potential energy-efficient alternative to conventional Artificial Neural Networks (ANNs) due to their inherent high-s…