Networks

End-to-end Structure-Aware Convolutional Networks for Knowledge Base Completion
文章目录研究问题背景动机模型思想模型框架实验部分评价
ConvolutionalAwareStructureNetworksCompletion
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GNN 2021(八) Heterogeneous Graph Structure Learning for Graph Neural Networks，AAAI
北邮石川老师团队的论文，又是有关异构图的。本文指出，异构图在现实中不可避免地是有噪声的或不完整的，因此，对于hgnn来说，学习异构图结构而不是仅仅依赖原始图结构是至关重要的。本文首次尝试学习最优的异构图结构用于hgnn，提出了一个新的框架
HeterogeneousGraphGNNStructureNetworks
admin1月前
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图神经网络论文阅读(五) Structure-Aware Convolutional Neural Networks，NIPS2018
本文的作者来自中科院自动化所以及中科院大学人工智能学院。为了拓展卷积操作到非欧图结构，本文提出了structure-aware convolution（结构感知卷积）将非欧式图与欧式图结构之间的差别抹平。从技术上讲，结构感知卷积中的滤波器
神经网络论文StructureAwareNetworks
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阅读笔记(五)：Dual Residual Networks Leveraging the Potential of Paired Operations for Image Restoration
Dual Residual Networks文章中去雨线部分的阅读笔记原文: Dual Residual Networks Leveraging the Potential of Paired Operations for Image
笔记ResidualNetworksLeveragingDual
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阅读笔记(三)：Dual Residual Networks Leveraging the Potential of Paired Operations for Image Restoration
Dual Residual Networks文章中去雾部分的阅读笔记原文: Dual Residual Networks Leveraging the Potential of Paired Operations for Image R
笔记ResidualNetworksLeveragingDual
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阅读笔记(四)：Dual Residual Networks Leveraging the Potential of Paired Operations for Image Restoration
Dual Residual Networks文章中去雨滴部分的阅读笔记原文: Dual Residual Networks Leveraging the Potential of Paired Operations for Image
笔记ResidualNetworksLeveragingDual
admin1月前
230

End-to-end Structure-Aware Convolutional Networks for Knowledge Base Completion

GNN 2021(八) Heterogeneous Graph Structure Learning for Graph Neural Networks，AAAI

图神经网络论文阅读(五) Structure-Aware Convolutional Neural Networks，NIPS2018

阅读笔记(五)：Dual Residual Networks Leveraging the Potential of Paired Operations for Image Restoration

阅读笔记(三)：Dual Residual Networks Leveraging the Potential of Paired Operations for Image Restoration

阅读笔记(四)：Dual Residual Networks Leveraging the Potential of Paired Operations for Image Restoration