Saved in:
| Main Authors: | Zhu, Alan, Ma, Jiaqi, Mei, Qiaozhu |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2502.15890 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Flexible Diffusion Scopes with Parameterized Laplacian for Heterophilic Graph Learning
by: Lu, Qincheng, et al.
Published: (2024)
by: Lu, Qincheng, et al.
Published: (2024)
A Spectral Framework for Evaluating Geodesic Distances Between Graphs
by: Shuvo, Soumen Sikder, et al.
Published: (2024)
by: Shuvo, Soumen Sikder, et al.
Published: (2024)
Bypassing Skip-Gram Negative Sampling: Dimension Regularization as a More Efficient Alternative for Graph Embeddings
by: Liu, David, et al.
Published: (2024)
by: Liu, David, et al.
Published: (2024)
NodeNAS: Node-Specific Graph Neural Architecture Search for Out-of-Distribution Generalization
by: Wang, Qiyi, et al.
Published: (2025)
by: Wang, Qiyi, et al.
Published: (2025)
MGDCF: Distance Learning via Markov Graph Diffusion for Neural Collaborative Filtering
by: Hu, Jun, et al.
Published: (2022)
by: Hu, Jun, et al.
Published: (2022)
Representation Learning on Heterophilic Graph with Directional Neighborhood Attention
by: Lu, Qincheng, et al.
Published: (2024)
by: Lu, Qincheng, et al.
Published: (2024)
From Primes to Paths: Enabling Fast Multi-Relational Graph Analysis
by: Bougiatiotis, Konstantinos, et al.
Published: (2024)
by: Bougiatiotis, Konstantinos, et al.
Published: (2024)
Biharmonic Distance of Graphs and its Higher-Order Variants: Theoretical Properties with Applications to Centrality and Clustering
by: Black, Mitchell, et al.
Published: (2024)
by: Black, Mitchell, et al.
Published: (2024)
Diffusion-based Negative Sampling on Graphs for Link Prediction
by: Nguyen, Trung-Kien, et al.
Published: (2024)
by: Nguyen, Trung-Kien, et al.
Published: (2024)
Heterophilous Distribution Propagation for Graph Neural Networks
by: Zheng, Zhuonan, et al.
Published: (2024)
by: Zheng, Zhuonan, et al.
Published: (2024)
When Do Graph Neural Networks Help with Node Classification? Investigating the Impact of Homophily Principle on Node Distinguishability
by: Luan, Sitao, et al.
Published: (2023)
by: Luan, Sitao, et al.
Published: (2023)
Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective
by: Lee, Soo Yong, et al.
Published: (2024)
by: Lee, Soo Yong, et al.
Published: (2024)
Transferability of Graph Neural Networks using Graphon and Sampling Theories
by: Neuman, A. Martina, et al.
Published: (2023)
by: Neuman, A. Martina, et al.
Published: (2023)
Path-based Explanation for Knowledge Graph Completion
by: Chang, Heng, et al.
Published: (2024)
by: Chang, Heng, et al.
Published: (2024)
Enhancing Graph Transformers with Hierarchical Distance Structural Encoding
by: Luo, Yuankai, et al.
Published: (2023)
by: Luo, Yuankai, et al.
Published: (2023)
Graph Learning under Distribution Shifts: A Comprehensive Survey on Domain Adaptation, Out-of-distribution, and Continual Learning
by: Wu, Man, et al.
Published: (2024)
by: Wu, Man, et al.
Published: (2024)
Reinforcement Learning Discovers Efficient Decentralized Graph Path Search Strategies
by: Pisacane, Alexei, et al.
Published: (2024)
by: Pisacane, Alexei, et al.
Published: (2024)
Graph Out-of-Distribution Generalization via Causal Intervention
by: Wu, Qitian, et al.
Published: (2024)
by: Wu, Qitian, et al.
Published: (2024)
PathMLP: Smooth Path Towards High-order Homophily
by: Zhou, Jiajun, et al.
Published: (2023)
by: Zhou, Jiajun, et al.
Published: (2023)
Uncertainty Estimation for Heterophilic Graphs Through the Lens of Information Theory
by: Fuchsgruber, Dominik, et al.
Published: (2025)
by: Fuchsgruber, Dominik, et al.
Published: (2025)
Out-of-Distribution Detection in Heterogeneous Graphs via Energy Propagation
by: Yin, Tao, et al.
Published: (2025)
by: Yin, Tao, et al.
Published: (2025)
GraphSB: Boosting Imbalanced Node Classification on Graphs through Structural Balance
by: Zhu, Chaofan, et al.
Published: (2025)
by: Zhu, Chaofan, et al.
Published: (2025)
Efficient Heterogeneous Graph Learning via Random Projection
by: Hu, Jun, et al.
Published: (2023)
by: Hu, Jun, et al.
Published: (2023)
An Efficient Loop and Clique Coarsening Algorithm for Graph Classification
by: Qi, Xiaorui, et al.
Published: (2024)
by: Qi, Xiaorui, et al.
Published: (2024)
FLASH: Flexible Learning of Adaptive Sampling from History in Temporal Graph Neural Networks
by: Feldman, Or, et al.
Published: (2025)
by: Feldman, Or, et al.
Published: (2025)
InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections
by: Qin, Meng, et al.
Published: (2025)
by: Qin, Meng, et al.
Published: (2025)
Efficient and Privacy-Preserved Link Prediction via Condensed Graphs
by: Long, Yunbo, et al.
Published: (2025)
by: Long, Yunbo, et al.
Published: (2025)
Graph Vertex Embeddings: Distance, Regularization and Community Detection
by: Nowak, Radosław, et al.
Published: (2024)
by: Nowak, Radosław, et al.
Published: (2024)
LEGO-Learn: Label-Efficient Graph Open-Set Learning
by: Xu, Haoyan, et al.
Published: (2024)
by: Xu, Haoyan, et al.
Published: (2024)
Efficient and Scalable Graph Generation through Iterative Local Expansion
by: Bergmeister, Andreas, et al.
Published: (2023)
by: Bergmeister, Andreas, et al.
Published: (2023)
Random Walk Diffusion for Efficient Large-Scale Graph Generation
by: Bernecker, Tobias, et al.
Published: (2024)
by: Bernecker, Tobias, et al.
Published: (2024)
Bipartite Graph Variational Auto-Encoder with Fair Latent Representation to Account for Sampling Bias in Ecological Networks
by: Anakok, Emre, et al.
Published: (2024)
by: Anakok, Emre, et al.
Published: (2024)
Efficient Learning on Large Graphs using a Densifying Regularity Lemma
by: Kouchly, Jonathan, et al.
Published: (2025)
by: Kouchly, Jonathan, et al.
Published: (2025)
HOT: Higher-Order Dynamic Graph Representation Learning with Efficient Transformers
by: Besta, Maciej, et al.
Published: (2023)
by: Besta, Maciej, et al.
Published: (2023)
SIGMA: An Efficient Heterophilous Graph Neural Network with Fast Global Aggregation
by: Liu, Haoyu, et al.
Published: (2023)
by: Liu, Haoyu, et al.
Published: (2023)
Robust Graph Contrastive Learning with Information Restoration
by: Zhu, Yulin, et al.
Published: (2023)
by: Zhu, Yulin, et al.
Published: (2023)
LAMP: Learnable Meta-Path Guided Adversarial Contrastive Learning for Heterogeneous Graphs
by: Li, Siqing, et al.
Published: (2024)
by: Li, Siqing, et al.
Published: (2024)
Graph Structure Prompt Learning: A Novel Methodology to Improve Performance of Graph Neural Networks
by: Huang, Zhenhua, et al.
Published: (2024)
by: Huang, Zhenhua, et al.
Published: (2024)
Echoless Label-Based Pre-computation for Memory-Efficient Heterogeneous Graph Learning
by: Hu, Jun, et al.
Published: (2025)
by: Hu, Jun, et al.
Published: (2025)
Statistical Guarantees for Link Prediction using Graph Neural Networks
by: Chung, Alan, et al.
Published: (2024)
by: Chung, Alan, et al.
Published: (2024)
Similar Items
-
Flexible Diffusion Scopes with Parameterized Laplacian for Heterophilic Graph Learning
by: Lu, Qincheng, et al.
Published: (2024) -
A Spectral Framework for Evaluating Geodesic Distances Between Graphs
by: Shuvo, Soumen Sikder, et al.
Published: (2024) -
Bypassing Skip-Gram Negative Sampling: Dimension Regularization as a More Efficient Alternative for Graph Embeddings
by: Liu, David, et al.
Published: (2024) -
NodeNAS: Node-Specific Graph Neural Architecture Search for Out-of-Distribution Generalization
by: Wang, Qiyi, et al.
Published: (2025) -
MGDCF: Distance Learning via Markov Graph Diffusion for Neural Collaborative Filtering
by: Hu, Jun, et al.
Published: (2022)