Enregistré dans:
| Auteurs principaux: | Jin, Yufei, Zhu, Xingquan |
|---|---|
| Format: | Preprint |
| Publié: |
2024
|
| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2405.01663 |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
HGEN: Heterogeneous Graph Ensemble Networks
par: Shen, Jiajun, et autres
Publié: (2025)
par: Shen, Jiajun, et autres
Publié: (2025)
Are We Measuring Oversmoothing in Graph Neural Networks Correctly?
par: Zhang, Kaicheng, et autres
Publié: (2025)
par: Zhang, Kaicheng, et autres
Publié: (2025)
On the Complexity of Optimal Graph Rewiring for Oversmoothing and Oversquashing in Graph Neural Networks
par: Chehreghani, Mostafa Haghir
Publié: (2026)
par: Chehreghani, Mostafa Haghir
Publié: (2026)
Oversmoothing: A Nightmare for Graph Contrastive Learning?
par: Li, Jintang, et autres
Publié: (2023)
par: Li, Jintang, et autres
Publié: (2023)
A Dynamical Systems-Inspired Pruning Strategy for Addressing Oversmoothing in Graph Neural Networks
par: Chakraborty, Biswadeep, et autres
Publié: (2024)
par: Chakraborty, Biswadeep, et autres
Publié: (2024)
Hierarchical Multi-Scale Graph Neural Networks: Scalable Heterophilous Learning with Oversmoothing and Oversquashing Mitigation
par: Hossen, Md Sazzad, et autres
Publié: (2026)
par: Hossen, Md Sazzad, et autres
Publié: (2026)
Oversmoothing as Representation Degeneracy in Neural Sheaf Diffusion
par: Dönmez, Arif, et autres
Publié: (2026)
par: Dönmez, Arif, et autres
Publié: (2026)
Tackling Oversmoothing in GNN via Graph Sparsification: A Truss-based Approach
par: Hossain, Tanvir, et autres
Publié: (2024)
par: Hossain, Tanvir, et autres
Publié: (2024)
LHGEL: Large Heterogeneous Graph Ensemble Learning using Batch View Aggregation
par: Shen, Jiajun, et autres
Publié: (2025)
par: Shen, Jiajun, et autres
Publié: (2025)
Delayed Bottlenecking: Alleviating Forgetting in Pre-trained Graph Neural Networks
par: Zhao, Zhe, et autres
Publié: (2024)
par: Zhao, Zhe, et autres
Publié: (2024)
Oversmoothing, Oversquashing, Heterophily, Long-Range, and more: Demystifying Common Beliefs in Graph Machine Learning
par: Arnaiz-Rodriguez, Adrian, et autres
Publié: (2025)
par: Arnaiz-Rodriguez, Adrian, et autres
Publié: (2025)
Unifying Adversarial Perturbation for Graph Neural Networks
par: Yang, Jinluan, et autres
Publié: (2025)
par: Yang, Jinluan, et autres
Publié: (2025)
Survey on Generalization Theory for Graph Neural Networks
par: Vasileiou, Antonis, et autres
Publié: (2025)
par: Vasileiou, Antonis, et autres
Publié: (2025)
STG4Traffic: A Survey and Benchmark of Spatial-Temporal Graph Neural Networks for Traffic Prediction
par: Luo, Xunlian, et autres
Publié: (2023)
par: Luo, Xunlian, et autres
Publié: (2023)
A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection
par: Jin, Ming, et autres
Publié: (2023)
par: Jin, Ming, et autres
Publié: (2023)
LPS-GNN : Deploying Graph Neural Networks on Graphs with 100-Billion Edges
par: Cheng, Xu, et autres
Publié: (2025)
par: Cheng, Xu, et autres
Publié: (2025)
Graph Neural Networks for Job Shop Scheduling Problems: A Survey
par: Smit, Igor G., et autres
Publié: (2024)
par: Smit, Igor G., et autres
Publié: (2024)
Causal Graph Neural Networks for Healthcare
par: Mesinovic, Munib, et autres
Publié: (2025)
par: Mesinovic, Munib, et autres
Publié: (2025)
A Survey on Graph Neural Networks for Fraud Detection in Ride Hailing Platforms
par: Hewageegana, Kanishka, et autres
Publié: (2025)
par: Hewageegana, Kanishka, et autres
Publié: (2025)
Graph Neural Networks in Multi-Omics Cancer Research: A Structured Survey
par: Zohari, Payam, et autres
Publié: (2025)
par: Zohari, Payam, et autres
Publié: (2025)
Laplacian-LoRA: Delaying Oversmoothing in Deep GCNs via Spectral Low-Rank Adaptation
par: Alisetti, Sai Vamsi
Publié: (2026)
par: Alisetti, Sai Vamsi
Publié: (2026)
A Comprehensive Survey on Self-Interpretable Neural Networks
par: Ji, Yang, et autres
Publié: (2025)
par: Ji, Yang, et autres
Publié: (2025)
A Unified Benchmark for Evaluating Knowledge Graph Construction Methods and Graph Neural Networks
par: Kabal, Othmane, et autres
Publié: (2026)
par: Kabal, Othmane, et autres
Publié: (2026)
Graph Unlearning: Efficient Node Removal in Graph Neural Networks
par: Guan, Faqian, et autres
Publié: (2025)
par: Guan, Faqian, et autres
Publié: (2025)
Graph Reinforcement Learning for Combinatorial Optimization: A Survey and Unifying Perspective
par: Darvariu, Victor-Alexandru, et autres
Publié: (2024)
par: Darvariu, Victor-Alexandru, et autres
Publié: (2024)
A Unified Kernel for Neural Network Learning
par: Zhang, Shao-Qun, et autres
Publié: (2024)
par: Zhang, Shao-Qun, et autres
Publié: (2024)
Spectro-Riemannian Graph Neural Networks
par: Grover, Karish, et autres
Publié: (2025)
par: Grover, Karish, et autres
Publié: (2025)
Why Do Neural Networks Forget: A Study of Collapse in Continual Learning
par: Zhu, Yunqin, et autres
Publié: (2026)
par: Zhu, Yunqin, et autres
Publié: (2026)
Heuristic Learning with Graph Neural Networks: A Unified Framework for Link Prediction
par: Zhang, Juzheng, et autres
Publié: (2024)
par: Zhang, Juzheng, et autres
Publié: (2024)
A Unified Framework for Generative Data Augmentation: A Comprehensive Survey
par: Chen, Yunhao, et autres
Publié: (2023)
par: Chen, Yunhao, et autres
Publié: (2023)
A Sugeno Integral View of Binarized Neural Network Inference
par: Baaj, Ismaïl, et autres
Publié: (2026)
par: Baaj, Ismaïl, et autres
Publié: (2026)
A Survey on Graph Neural Networks for Remaining Useful Life Prediction: Methodologies, Evaluation and Future Trends
par: Wang, Yucheng, et autres
Publié: (2024)
par: Wang, Yucheng, et autres
Publié: (2024)
Generalization in Neural Networks: A Broad Survey
par: Rohlfs, Chris
Publié: (2022)
par: Rohlfs, Chris
Publié: (2022)
A Survey on Knowledge Editing of Neural Networks
par: Mazzia, Vittorio, et autres
Publié: (2023)
par: Mazzia, Vittorio, et autres
Publié: (2023)
A Survey of Out-of-distribution Generalization for Graph Machine Learning from a Causal View
par: Ma, Jing
Publié: (2024)
par: Ma, Jing
Publié: (2024)
Soft-Evidence Fused Graph Neural Network for Cancer Driver Gene Identification across Multi-View Biological Graphs
par: Chen, Bang, et autres
Publié: (2025)
par: Chen, Bang, et autres
Publié: (2025)
LineMVGNN: Anti-Money Laundering with Line-Graph-Assisted Multi-View Graph Neural Networks
par: Poon, Chung-Hoo, et autres
Publié: (2026)
par: Poon, Chung-Hoo, et autres
Publié: (2026)
Unified Sparse-Matrix Representations for Diverse Neural Architectures
par: Zhu, Yuzhou
Publié: (2025)
par: Zhu, Yuzhou
Publié: (2025)
Causal Graph Neural Networks for Wildfire Danger Prediction
par: Zhao, Shan, et autres
Publié: (2024)
par: Zhao, Shan, et autres
Publié: (2024)
Graphs Unveiled: Graph Neural Networks and Graph Generation
par: Kovács, László, et autres
Publié: (2024)
par: Kovács, László, et autres
Publié: (2024)
Documents similaires
-
HGEN: Heterogeneous Graph Ensemble Networks
par: Shen, Jiajun, et autres
Publié: (2025) -
Are We Measuring Oversmoothing in Graph Neural Networks Correctly?
par: Zhang, Kaicheng, et autres
Publié: (2025) -
On the Complexity of Optimal Graph Rewiring for Oversmoothing and Oversquashing in Graph Neural Networks
par: Chehreghani, Mostafa Haghir
Publié: (2026) -
Oversmoothing: A Nightmare for Graph Contrastive Learning?
par: Li, Jintang, et autres
Publié: (2023) -
A Dynamical Systems-Inspired Pruning Strategy for Addressing Oversmoothing in Graph Neural Networks
par: Chakraborty, Biswadeep, et autres
Publié: (2024)