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04/09/2023
Class-Imbalanced Learning on Graphs: A Survey
The rapid advancement in data-driven research has increased the demand f...
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02/01/2023
Knowledge Distillation on Graphs: A Survey
Graph Neural Networks (GNNs) have attracted tremendous attention by demo...
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11/29/2022
FakeEdge: Alleviate Dataset Shift in Link Prediction
Link prediction is a crucial problem in graph-structured data. Due to th...
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10/12/2022
Boosting Graph Neural Networks via Adaptive Knowledge Distillation
Graph neural networks (GNNs) have shown remarkable performance on divers...
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10/01/2022
Diving into Unified Data-Model Sparsity for Class-Imbalanced Graph Representation Learning
Even pruned by the state-of-the-art network compression methods, Graph N...
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08/22/2022
NOSMOG: Learning Noise-robust and Structure-aware MLPs on Graphs
While Graph Neural Networks (GNNs) have demonstrated their efficacy in d...
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08/21/2022
Heterogeneous Graph Masked Autoencoders
Generative self-supervised learning (SSL), especially masked autoencoder...
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07/08/2022
Graph-based Molecular Representation Learning
Molecular representation learning (MRL) is a key step to build the conne...
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05/24/2022
Recipe2Vec: Multi-modal Recipe Representation Learning with Graph Neural Networks
Learning effective recipe representations is essential in food studies. ...
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05/24/2022
RecipeRec: A Heterogeneous Graph Learning Model for Recipe Recommendation
Recipe recommendation systems play an essential role in helping people d...
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01/27/2019
