Graph Neural Networks with Adaptive ResidualXiaorui Liu (Michigan State University) · Jiayuan Ding (Michigan State University) · Wei Jin (Michigan State University) · Han Xu (Michigan State University) · Yao Ma (New Jersey Institute of Technology) · Jiliang Tang (Michigan State University) EI...
^Wei Jin, Yao Ma, Xiaorui Liu, Xianfeng Tang, Suhang Wang, and Jiliang Tang. Graph structure learning for robust graph neural networks. In KDD, 2020. ^Xiaorui Liu, Jiayuan Ding, Wei Jin, Han Xu, Yao Ma, Zitao Liu, and Jiliang Tang. Graph neural networks with adaptive residual. NeurIPS...
36、Graph neural networks with adaptive residual. NeurIPS, 2021. 37、On the unreasonable effectiveness of feature propagation in learning on graphs with missing node features 38、Graph convolutional networks for graphs containing missing features. FGCS, 2021. ...
Graph neural networks with generated parameters for relation extraction Graph neural networks with generated parameters for relation extraction (2019) Google Scholar 42. Y. Zhang, V. Zhong, D. Chen, G. Angeli, C. D. Manning Position-aware attention and supervised data improve slot filling (2017...
GeniePath: Graph Neural Networks with Adaptive Receptive Paths. AAAI 2019. paper Ziqi Liu, Chaochao Chen, Longfei Li, Jun Zhou, Xiaolong Li, Le Song, Yuan Qi. Gaussian-Induced Convolution for Graphs. AAAI 2019. paper Jiatao Jiang, Zhen Cui, Chunyan Xu, Jian Yang. Fisher-Bures Adversary Gra...
Structure-adaptive graph neural network with temporal representation and residual connections World Wide Web (2023) WuC. et al. Fedgnn: Federated graph neural network for privacy-preserving recommendation (2021)View more references Cited by (2) Structural graph federated learning: Exploiting high-dimensi...
GeniePath: Graph Neural Networks with Adaptive Receptive Paths. AAAI 2019. paper Ziqi Liu, Chaochao Chen, Longfei Li, Jun Zhou, Xiaolong Li, Le Song, Yuan Qi. Gaussian-Induced Convolution for Graphs. AAAI 2019. paper Jiatao Jiang, Zhen Cui, Chunyan Xu, Jian Yang. Fisher-Bures Adversary Gra...
Chapter 5 - Adaptive graph convolutional neural network and its biomedical applications 来自 dx.doi.org 喜欢 0 阅读量: 14 作者:J Huang,R Li 出版社: Elsevier Inc. 关键词: Neural networks kernel residual graphs DeepGraphSurv graph attentional network ...
4. Adaptive Initial Residual (AIR) P 操作间的 AIR 旨在缓解 over-smoothing 并以节点自适应的方式利用深层信息,T 操作间的 AIR 主要目的是缓解 model degradation。 4.1 AIR Between P and T Operations 在P 操作过程中的节点自适应分数计算机制: \alpha_i^{(l)} = \mathrm{sigmoid}\left[(\mathbf{H}...
Schur Nets: exploiting local structure for equivariance in higher order graph neural networks Graph Edit Distance with General Costs Using Neural Set Divergence Deep Graph Neural Networks via Posteriori-Sampling-based Node-Adaptative Residual Module Can Graph Learning Improve Task Planning? EGSST: Event...