23 citations · 57 across the 7 of their papers we have counts for
7 papers · 1 filter
Brain-inspired Multilayer Perceptron with Spiking Neurons
Wenshuo Li, Hanting Chen, Jianyuan Guo +2
Recently, Multilayer Perceptron (MLP) becomes the hotspot in the field of computer vision tasks. Without inductive bias, MLPs perform well on feature extraction and achieve amazing…
Universal Adder Neural Networks
Hanting Chen, Yunhe Wang, Chang Xu +3
Compared with cheap addition operation, multiplication operation is of much higher computation complexity. The widely-used convolutions in deep neural networks are exactly cross-co…
Pre-Trained Image Processing Transformer
Hanting Chen, Yunhe Wang, Tianyu Guo +7
As the computing power of modern hardware is increasing strongly, pre-trained deep learning models (e.g., BERT, GPT-3) learned on large-scale datasets have shown their effectivenes…
A Semi-Supervised Assessor of Neural Architectures
Yehui Tang, Yunhe Wang, Yixing Xu +6
Neural architecture search (NAS) aims to automatically design deep neural networks of satisfactory performance. Wherein, architecture performance predictor is critical to efficient…
Distilling portable Generative Adversarial Networks for Image Translation
Hanting Chen, Yunhe Wang, Han Shu +5
Despite Generative Adversarial Networks (GANs) have been widely used in various image-to-image translation tasks, they can be hardly applied on mobile devices due to their heavy co…
Widening and Squeezing: Towards Accurate and Efficient QNNs
Chuanjian Liu, Kai Han, Yunhe Wang +3
Quantization neural networks (QNNs) are very attractive to the industry because their extremely cheap calculation and storage overhead, but their performance is still worse than th…