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Graph neural networks have emerged as a leading architecture for many graph-level tasks, such as graph classification and graph generation.
Convolutional networks on graphs for learning molecular fingerprints
David Duvenaud, et al · 2015
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Diffusion-convolutional neural networks
James Atwood et al · 2016
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Gated graph sequence neural networks
Yujia Li, et al · 2016
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Order matters: Sequence to sequence for sets
Oriol Vinyals, et al · 2016
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Semi-supervised classification with graph convolutional networks
Thomas N. Kipf et al · 2017
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Dynamic edge-conditioned filters in convolutional neural networks on graphs
Martin Simonovsky et al · 2017
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Towards sparse hierarchical graph classifiers
Cătălina Cangea, et al · 2018
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Splinecnn: Fast geometric deep learning with continuous b-spline kernels
Matthias Fey, et al · 2018
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Hybrid approach of relation network and localized graph convolutional filtering for breast cancer subtype classification
Sungmin Rhee, et al · 2018
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Mining point cloud local structures by kernel correlation and graph pooling
Y. Shen, et al · 2018
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Hierarchical graph representation learning with differentiable pooling
Zhitao Ying, et al · 2018
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An end-to-end deep learning architecture for graph classification
Muhan Zhang, et al · 2018
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A non-negative factorization approach to node pooling in graph convolutional neural networks
Davide Bacciu et al · 2019
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Unsupervised inductive graph-level representation learning via graph-graph proximity
Yunsheng Bai, et al · 2019
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Are powerful graph neural nets necessary? a dissection on graph classification
Ting Chen, et al · 2019
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Edge contraction pooling for graph neural networks
Frederik Diehl · 2019
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Graph u-nets
Hongyang Gao et al · 2019
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Learning graph pooling and hybrid convolutional operations for text representations
Hongyang Gao, et al · 2019
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Multi-task learning on graphs with node and graph level labels
Chester Holtz, et al · 2019
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Attpool: Towards hierarchical feature representation in graph convolutional networks via attention mechanism
Jingjia Huang, et al · 2019
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Understanding attention and generalization in graph neural networks
Boris Knyazev, et al · 2019
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Self-attention graph pooling
Junhyun Lee, et al · 2019
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Graph convolutional networks with eigenpooling
Yao Ma, et al · 2019
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Relational pooling for graph representations
Ryan Murphy, et al · 2019
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Universal readout for graph convolutional neural networks
Nicolò Navarin, et al · 2019
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Towards interpretable sparse graph representation learning with laplacian pooling
Emmanuel Noutahi, et al · 2019
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Demo-net: Degree-specific graph neural networks for node and graph classification
Jun Wu, et al · 2019
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How powerful are graph neural networks?
Keyulu Xu, et al · 2019
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Representation learning of histopathology images using graph neural networks
Mohammed Adnan, et al · 2020
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Spectral clustering with graph neural networks for graph pooling
Filippo Maria Bianchi, et al · 2020
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Hierarchical representation learning in graph neural networks with node decimation pooling
Filippo Maria Bianchi, et al · 2020
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Deep graph mapper: Seeing graphs through the neural lens
Cristian Bodnar, et al · 2020
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Hapgn: Hierarchical attentive pooling graph network for point cloud segmentation
Chaofan Chen, et al · 2020
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Can graph neural networks count substructures?
Zhengdao Chen, et al · 2020
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Benchmarking graph neural networks
Vijay Prakash Dwivedi, et al · 2020
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A fair comparison of graph neural networks for graph classification
Federico Errica, et al · 2020
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Structured self-attention architecture for graph-level representation learning
Xiaolong Fan, et al · 2020
Cited alongside, same era.
Lookhops: light multi-order convolution and pooling for graph classification
Zhangyang Gao, et al · 2020
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Open graph benchmark: Datasets for machine learning on graphs
Weihua Hu, et al · 2020
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Memory-based graph networks
Amir Hosein Khasahmadi, et al · 2020
Cited alongside, same era.
Graph pooling with representativeness
Juanhui Li, et al · 2020
Cited alongside, same era.
Graph cross networks with vertex infomax pooling
Maosen Li, et al · 2020
Learning dynamic graph representation of brain connectome with spatio-temporal attention
Byung-Hoon Kim, et al · 2021
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Learnable structural semantic readout for graph classification
Dongha Lee, et al · 2021
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Deconvolutional networks on graph data
Jia Li, et al · 2021
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Structure-aware interactive graph neural networks for the prediction of protein-ligand binding affinity
Shuangli Li, et al · 2021
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Braingnn: Interpretable brain graph neural network for fmri analysis
Xiaoxiao Li, et al · 2021
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Hierarchical adaptive pooling by capturing high-order dependency for graph representation learning
Ning Liu, et al · 2021
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Cited alongside, same era.
Pooling regularized graph neural network for fmri biomarker analysis
Xiaoxiao Li, et al · 2020
Cited alongside, same era.
Mxpool: Multiplex pooling for hierarchical graph representation learning
Yanyan Liang, et al · 2020
Cited alongside, same era.
Deep learning for community detection: progress, challenges and opportunities
Fanzhen Liu, et al · 2020
Cited alongside, same era.
Path integral based convolution and pooling for graph neural networks
Zheng Ma, et al · 2020
Cited alongside, same era.
Analyzing unaligned multimodal sequence via graph convolution and graph pooling fusion
Sijie Mai, et al · 2020
Cited alongside, same era.
Rethinking pooling in graph neural networks
Diego Mesquita, et al · 2020
Cited alongside, same era.
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Learning hierarchical review graph representations for recommendation
Y. Liu, et al · 2021
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A comprehensive survey on graph anomaly detection with deep learning
Xiaoxiao Ma, et al · 2021
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KGPool: Dynamic knowledge graph context selection for relation extraction
Abhishek Nadgeri, et al · 2021
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Li Pan, et al · 2021
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Graph pooling via coarsened graph infomax
Yunsheng Pang, et al · 2021
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Dropgnn: Random dropouts increase the expressiveness of graph neural networks
Pál András Papp, et al · 2021
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Structure-aware hierarchical graph pooling using information bottleneck
Kashob Kumar Roy, et al · 2021
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Hierarchical graph representation learning with local capsule pooling
Zidong Su, et al · 2021
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Hemlata Tak, et al · 2021
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Commpool: An interpretable graph pooling framework for hierarchical graph representation learning
Haoteng Tang, et al · 2021
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Papooling: Graph-based position adaptive aggregation of local geometry in point clouds
Jie Wang, et al · 2021
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Pooling architecture search for graph classification
Lanning Wei, et al · 2021
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User-as-graph: User modeling with heterogeneous graph pooling for news recommendation
Chuhan Wu, et al · 2021
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How neural networks extrapolate: From feedforward to graph neural networks
Keyulu Xu, et al · 2021
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Hierarchical graph capsule network
Jinyu Yang, et al · 2021
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Decoupling the depth and scope of graph neural networks
Hanqing Zeng, et al · 2021
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Hierarchical multi-view graph pooling with structure learning
Zhen Zhang, et al · 2021
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Distribution knowledge embedding for graph pooling
Kaixuan Chen, et al · 2022
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Higher-order clustering and pooling for graph neural networks
Alexandre Duval et al · 2022
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Learnable pooling in graph convolutional networks for brain surface analysis
Karthik Gopinath, et al · 2022
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Multi-level attention pooling for graph neural networks: Unifying graph representations with multiple localities
Takeshi D. Itoh, et al · 2022
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On exploring node-feature and graph-structure diversities for node drop graph pooling, 2022
Chuang Liu, et al · 2022
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Unsupervised hierarchical graph pooling via substructure-sensitive mutual information maximization
Ning Liu, et al · 2022
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Higil: Hierarchical graph inference learning for fact checking
Qianren Mao, et al · 2022
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Dynamic emotion modeling with learnable graphs and graph inception network
Amir Shirian, et al · 2022
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Structural entropy guided graph hierarchical pooling
Junran Wu et al · 2022
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Multi-grained semantics-aware graph neural networks
Zhiqiang Zhong, et al · 2022
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The expressive power of pooling in graph neural networks
Filippo Maria Bianchi et al · 2023
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Masked graph auto-encoder constrained graph pooling
Chuang Liu, et al · 2023
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