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04/04/2023
RARE: Robust Masked Graph Autoencoder
Masked graph autoencoder (MGAE) has emerged as a promising self-supervis...
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03/14/2023
GANN: Graph Alignment Neural Network for Semi-Supervised Learning
Graph neural networks (GNNs) have been widely investigated in the field ...
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02/15/2023
Revisiting Initializing Then Refining: An Incomplete and Missing Graph Imputation Network
With the development of various applications, such as social networks an...
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01/03/2023
Cluster-guided Contrastive Graph Clustering Network
Benefiting from the intrinsic supervision information exploitation capab...
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12/16/2022
Hard Sample Aware Network for Contrastive Deep Graph Clustering
Contrastive deep graph clustering, which aims to divide nodes into disjo...
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11/19/2022
Relational Symmetry based Knowledge Graph Contrastive Learning
Knowledge graph embedding (KGE) aims to learn powerful representations t...
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05/30/2022
Align then Fusion: Generalized Large-scale Multi-view Clustering with Anchor Matching Correspondences
Multi-view anchor graph clustering selects representative anchors to avo...
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02/25/2022
Improved Dual Correlation Reduction Network
Deep graph clustering, which aims to reveal the underlying graph structu...
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12/29/2021
Deep Graph Clustering via Dual Correlation Reduction
Deep graph clustering, which aims to reveal the underlying graph structu...
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12/09/2021
Siamese Attribute-missing Graph Auto-encoder
Graph representation learning (GRL) on attribute-missing graphs, which i...
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05/01/2021
Multi-view Clustering with Deep Matrix Factorization and Global Graph Refinement
Multi-view clustering is an important yet challenging task in machine le...
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03/21/2021
Deep Distribution-preserving Incomplete Clustering with Optimal Transport
Clustering is a fundamental task in the computer vision and machine lear...
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12/15/2020
Deep Fusion Clustering Network
Deep clustering is a fundamental yet challenging task for data analysis....
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07/26/2019
