42 citations · 265 across the 30 of their papers we have counts for
6 papers · 1 filter
Post-training Quantization on Diffusion Models
Yuzhang Shang, Zhihang Yuan, Bin Xie +2
Denoising diffusion (score-based) generative models have recently achieved significant accomplishments in generating realistic and diverse data. These approaches define a forward d…
ENAS4D: Efficient Multi-stage CNN Architecture Search for Dynamic Inference
Zhihang Yuan, Xin Liu, Bingzhe Wu +1
Dynamic inference is a feasible way to reduce the computational cost of convolutional neural network(CNN), which can dynamically adjust the computation for each input sample. One o…
S2DNAS:Transforming Static CNN Model for Dynamic Inference via Neural Architecture Search
Zhihang Yuan, Bingzhe Wu, Zheng Liang +3
Recently, dynamic inference has emerged as a promising way to reduce the computational cost of deep convolutional neural network (CNN). In contrast to static methods (e.g. weight p…
P3SGD: Patient Privacy Preserving SGD for Regularizing Deep CNNs in Pathological Image Classification
Bingzhe Wu, Shiwan Zhao, Guangyu Sun +4
Recently, deep convolutional neural networks (CNNs) have achieved great success in pathological image classification. However, due to the limited number of labeled pathological ima…
G2C: A Generator-to-Classifier Framework Integrating Multi-Stained Visual Cues for Pathological Glomerulus Classification
Bingzhe Wu, Xiaolu Zhang, Shiwan Zhao +4
Pathological glomerulus classification plays a key role in the diagnosis of nephropathy. As the difference between different subcategories is subtle, doctors often refer to slides…
SRPGAN: Perceptual Generative Adversarial Network for Single Image Super Resolution
Bingzhe Wu, Haodong Duan, Zhichao Liu +1
Single image super resolution (SISR) is to reconstruct a high resolution image from a single low resolution image. The SISR task has been a very attractive research topic over the…