Zhengyang Wang

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Washington State University ∙ Texas A&M University

Second-Order Pooling for Graph Neural Networks

Graph neural networks have achieved great success in learning node repre...
07/20/2020 ∙ by Zhengyang Wang, et al. ∙ 90 ∙ share

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Kronecker Attention Networks

Attention operators have been applied on both 1-D data like texts and hi...
07/16/2020 ∙ by Hongyang Gao, et al. ∙ 54 ∙ share

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Non-Local Graph Neural Networks

Modern graph neural networks (GNNs) learn node embeddings through multil...
05/29/2020 ∙ by Meng Liu, et al. ∙ 34 ∙ share

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Global Transformer U-Nets for Label-Free Prediction of Fluorescence Images

Visualizing the details of different cellular structures is of great imp...
07/01/2019 ∙ by YI LIU, et al. ∙ 0 ∙ share

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Global Deep Learning Methods for Multimodality Isointense Infant Brain Image Segmentation

An important step in early brain development study is to perform automat...
12/10/2018 ∙ by Zhengyang Wang, et al. ∙ 0 ∙ share

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ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions

Convolutional neural networks (CNNs) have shown great capability of solv...
09/05/2018 ∙ by Hongyang Gao, et al. ∙ 0 ∙ share

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Smoothed Dilated Convolutions for Improved Dense Prediction

Dilated convolutions, also known as atrous convolutions, have been widel...
08/27/2018 ∙ by Zhengyang Wang, et al. ∙ 0 ∙ share

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Large-Scale Learnable Graph Convolutional Networks

Convolutional neural networks (CNNs) have achieved great success on grid...
08/12/2018 ∙ by Hongyang Gao, et al. ∙ 0 ∙ share

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Learning Convolutional Text Representations for Visual Question Answering

Visual question answering is a recently proposed artificial intelligence...
05/18/2017 ∙ by Zhengyang Wang, et al. ∙ 0 ∙ share

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Spatial Variational Auto-Encoding via Matrix-Variate Normal Distributions

The key idea of variational auto-encoders (VAEs) resembles that of tradi...
05/18/2017 ∙ by Zhengyang Wang, et al. ∙ 0 ∙ share

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Pixel Deconvolutional Networks

Deconvolutional layers have been widely used in a variety of deep models...
05/18/2017 ∙ by Hongyang Gao, et al. ∙ 0 ∙ share

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Zhengyang Wang

Featured Co-authors

YI LIU

Dinggang Shen

Shuiwang Ji

Hongyang Gao

Hao Yuan

Na Zou

Meng Liu

Second-Order Pooling for Graph Neural Networks

Kronecker Attention Networks

Non-Local Graph Neural Networks

Global Transformer U-Nets for Label-Free Prediction of Fluorescence Images

Global Deep Learning Methods for Multimodality Isointense Infant Brain Image Segmentation

ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions

Smoothed Dilated Convolutions for Improved Dense Prediction

Large-Scale Learnable Graph Convolutional Networks

Learning Convolutional Text Representations for Visual Question Answering

Spatial Variational Auto-Encoding via Matrix-Variate Normal Distributions

Pixel Deconvolutional Networks