Resurrecting Label Propagation for Graphs with Heterophily and Label Noise
Fuente:
arXiv
Saved in:
| Main Authors: | Cheng, Yao, Shan, Caihua, Shen, Yifei, Li, Xiang, Luo, Siqiang, Li, Dongsheng |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Survey on Learning from Graphs with Heterophily: Recent Advances and Future Directions
by: Gong, Chenghua, et al.
Published: (2024)
by: Gong, Chenghua, et al.
Published: (2024)
Towards Graph Foundation Models: Training on Knowledge Graphs Enables Transferability to General Graphs
by: Wang, Kai, et al.
Published: (2024)
by: Wang, Kai, et al.
Published: (2024)
Omni-DNA: A Unified Genomic Foundation Model for Cross-Modal and Multi-Task Learning
by: Li, Zehui, et al.
Published: (2025)
by: Li, Zehui, et al.
Published: (2025)
Modality-free Graph In-context Alignment
by: Zhuo, Wei, et al.
Published: (2026)
by: Zhuo, Wei, et al.
Published: (2026)
How Do Large Language Models Understand Graph Patterns? A Benchmark for Graph Pattern Comprehension
by: Dai, Xinnan, et al.
Published: (2024)
by: Dai, Xinnan, et al.
Published: (2024)
MoSE: Unveiling Structural Patterns in Graphs via Mixture of Subgraph Experts
by: Ye, Junda, et al.
Published: (2025)
by: Ye, Junda, et al.
Published: (2025)
Oldie but Goodie: Re-illuminating Label Propagation on Graphs with Partially Observed Features
by: Yun, Sukwon, et al.
Published: (2025)
by: Yun, Sukwon, et al.
Published: (2025)
PTCL: Pseudo-Label Temporal Curriculum Learning for Label-Limited Dynamic Graph
by: Zhang, Shengtao, et al.
Published: (2025)
by: Zhang, Shengtao, et al.
Published: (2025)
Graph Negative Feedback Bias Correction Framework for Adaptive Heterophily Modeling
by: Lv, Jiaqi, et al.
Published: (2026)
by: Lv, Jiaqi, et al.
Published: (2026)
Learning under Temporal Label Noise
by: Nagaraj, Sujay, et al.
Published: (2024)
by: Nagaraj, Sujay, et al.
Published: (2024)
Revealing Modular Gradient Noise Imbalance in LLMs: Calibrating Adam via Signal-to-Noise Ratio
by: Wen, Ziqing, et al.
Published: (2026)
by: Wen, Ziqing, et al.
Published: (2026)
HeterSEED: Semantics-Structure Decoupling for Heterogeneous Graph Learning under Heterophily
by: Li, Xinyi, et al.
Published: (2026)
by: Li, Xinyi, et al.
Published: (2026)
Disentangling Homophily and Heterophily in Multimodal Graph Clustering
by: Guo, Zhaochen, et al.
Published: (2025)
by: Guo, Zhaochen, et al.
Published: (2025)
When Noisy Labels Meet Class Imbalance on Graphs: A Graph Augmentation Method with LLM and Pseudo Label
by: Xia, Riting, et al.
Published: (2025)
by: Xia, Riting, et al.
Published: (2025)
Impact of Label Noise on Learning Complex Features
by: Vashisht, Rahul, et al.
Published: (2024)
by: Vashisht, Rahul, et al.
Published: (2024)
Correcting Noisy Multilabel Predictions: Modeling Label Noise through Latent Space Shifts
by: Huang, Weipeng, et al.
Published: (2025)
by: Huang, Weipeng, et al.
Published: (2025)
Delving into Instance-Dependent Label Noise in Graph Data: A Comprehensive Study and Benchmark
by: Kim, Suyeon, et al.
Published: (2025)
by: Kim, Suyeon, et al.
Published: (2025)
DiRW: Path-Aware Digraph Learning for Heterophily
by: Su, Daohan, et al.
Published: (2024)
by: Su, Daohan, et al.
Published: (2024)
Label Noise Robustness for Domain-Agnostic Fair Corrections via Nearest Neighbors Label Spreading
by: Stromberg, Nathan, et al.
Published: (2024)
by: Stromberg, Nathan, et al.
Published: (2024)
What Makes a Good Diffusion Planner for Decision Making?
by: Lu, Haofei, et al.
Published: (2025)
by: Lu, Haofei, et al.
Published: (2025)
TMLC-Net: Transferable Meta Label Correction for Noisy Label Learning
by: Li, Mengyang
Published: (2025)
by: Li, Mengyang
Published: (2025)
Modeling Heterophily in Multiplex Graphs: An Adaptive Approach for Node Classification
by: Abdous, Kamel, et al.
Published: (2026)
by: Abdous, Kamel, et al.
Published: (2026)
Adaptive Heterogeneous Graph Neural Networks: Bridging Heterophily and Heterogeneity
by: Chen, Qin, et al.
Published: (2025)
by: Chen, Qin, et al.
Published: (2025)
When Heterophily Meets Heterogeneous Graphs: Latent Graphs Guided Unsupervised Representation Learning
by: Shen, Zhixiang, et al.
Published: (2024)
by: Shen, Zhixiang, et al.
Published: (2024)
Robust Deep Hawkes Process under Label Noise of Both Event and Occurrence
by: Tan, Xiaoyu, et al.
Published: (2024)
by: Tan, Xiaoyu, et al.
Published: (2024)
Nested Graph Pseudo-Label Refinement for Noisy Label Domain Adaptation Learning
by: Wang, Yingxu, et al.
Published: (2025)
by: Wang, Yingxu, et al.
Published: (2025)
Graph Propagation Transformer for Graph Representation Learning
by: Chen, Zhe, et al.
Published: (2023)
by: Chen, Zhe, et al.
Published: (2023)
Dynamical Label Augmentation and Calibration for Noisy Electronic Health Records
by: Li, Yuhao, et al.
Published: (2025)
by: Li, Yuhao, et al.
Published: (2025)
FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning
by: Ji, Xinyuan, et al.
Published: (2024)
by: Ji, Xinyuan, et al.
Published: (2024)
Enhancing Distribution and Label Consistency for Graph Out-of-Distribution Generalization
by: Wang, Song, et al.
Published: (2025)
by: Wang, Song, et al.
Published: (2025)
Learning from Label Proportions: Bootstrapping Supervised Learners via Belief Propagation
by: Havaldar, Shreyas, et al.
Published: (2023)
by: Havaldar, Shreyas, et al.
Published: (2023)
Online Multi-Label Classification under Noisy and Changing Label Distribution
by: Zou, Yizhang, et al.
Published: (2024)
by: Zou, Yizhang, et al.
Published: (2024)
Hide and Seek in Noise Labels: Noise-Robust Collaborative Active Learning with LLM-Powered Assistance
by: Yuan, Bo, et al.
Published: (2025)
by: Yuan, Bo, et al.
Published: (2025)
The Resurrection of the ReLU
by: Horuz, Coşku Can, et al.
Published: (2025)
by: Horuz, Coşku Can, et al.
Published: (2025)
An Unbiased Risk Estimator for Partial Label Learning with Augmented Classes
by: Hu, Jiayu, et al.
Published: (2024)
by: Hu, Jiayu, et al.
Published: (2024)
The Malignant Tail: Spectral Segregation of Label Noise in Over-Parameterized Networks
by: Wang, Zice
Published: (2026)
by: Wang, Zice
Published: (2026)
Exploring Loss Design Techniques For Decision Tree Robustness To Label Noise
by: Sztukiewicz, Lukasz, et al.
Published: (2024)
by: Sztukiewicz, Lukasz, et al.
Published: (2024)
On the Learning Dynamics of Two-layer Linear Networks with Label Noise SGD
by: Zhang, Tongcheng, et al.
Published: (2026)
by: Zhang, Tongcheng, et al.
Published: (2026)
Label Noise Robustness of Conformal Prediction
by: Einbinder, Bat-Sheva, et al.
Published: (2022)
by: Einbinder, Bat-Sheva, et al.
Published: (2022)
DHIL-GT: Scalable Graph Transformer with Decoupled Hierarchy Labeling
by: Liao, Ningyi, et al.
Published: (2024)
by: Liao, Ningyi, et al.
Published: (2024)
Similar Items
-
A Survey on Learning from Graphs with Heterophily: Recent Advances and Future Directions
by: Gong, Chenghua, et al.
Published: (2024) -
Towards Graph Foundation Models: Training on Knowledge Graphs Enables Transferability to General Graphs
by: Wang, Kai, et al.
Published: (2024) -
Omni-DNA: A Unified Genomic Foundation Model for Cross-Modal and Multi-Task Learning
by: Li, Zehui, et al.
Published: (2025) -
Modality-free Graph In-context Alignment
by: Zhuo, Wei, et al.
Published: (2026) -
How Do Large Language Models Understand Graph Patterns? A Benchmark for Graph Pattern Comprehension
by: Dai, Xinnan, et al.
Published: (2024)