:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Xia, Donglin, Wang, Xiao, Liu, Nian, Shi, Chuan
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2403.03599
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Hierarchical Contrastive Learning Enhanced Heterogeneous Graph Neural Network
by: Liu, Nian, et al.
Published: (2023)

Provable Training for Graph Contrastive Learning
by: Yu, Yue, et al.
Published: (2023)

Generalizing Graph Neural Networks on Out-Of-Distribution Graphs
by: Fan, Shaohua, et al.
Published: (2021)

Graph Contrastive Invariant Learning from the Causal Perspective
by: Mo, Yanhu, et al.
Published: (2024)

On the Topology Awareness and Generalization Performance of Graph Neural Networks
by: Su, Junwei, et al.
Published: (2024)

On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks
by: Su, Junwei, et al.
Published: (2025)

Probability Passing for Graph Neural Networks: Graph Structure and Representations Joint Learning
by: Wang, Ziyan, et al.
Published: (2024)

Homomorphism Expressivity of Spectral Invariant Graph Neural Networks
by: Gai, Jingchu, et al.
Published: (2025)

Directed Acyclic Graph Structure Learning from Dynamic Graphs
by: Fan, Shaohua, et al.
Published: (2022)

Learning Invariant Visual Representations for Planning with Joint-Embedding Predictive World Models
by: Toso, Leonardo F., et al.
Published: (2026)

Graph Coarsening via Supervised Granular-Ball for Scalable Graph Neural Network Training
by: Xia, Shuyin, et al.
Published: (2024)

FairSIN: Achieving Fairness in Graph Neural Networks through Sensitive Information Neutralization
by: Yang, Cheng, et al.
Published: (2024)

Cross-View Graph Consistency Learning for Invariant Graph Representations
by: Chen, Jie, et al.
Published: (2023)

Causal Neighbourhood Learning for Invariant Graph Representations
by: Job, Simi, et al.
Published: (2026)

Exploring Task Unification in Graph Representation Learning via Generative Approach
by: Hu, Yulan, et al.
Published: (2024)

Invariant-Stratified Propagation for Expressive Graph Neural Networks
by: Hevapathige, Asela, et al.
Published: (2026)

DPGNN: Dual-Perception Graph Neural Network for Representation Learning
by: Zhou, Li, et al.
Published: (2021)

Graph Neural Networks for Learning Equivariant Representations of Neural Networks
by: Kofinas, Miltiadis, et al.
Published: (2024)

Enhancing Size Generalization in Graph Neural Networks through Disentangled Representation Learning
by: Huang, Zheng, et al.
Published: (2024)

Bounded Graph Clustering with Graph Neural Networks
by: Neocosmos, Kibidi, et al.
Published: (2025)

Learning Social Graph for Inactive User Recommendation
by: Liu, Nian, et al.
Published: (2024)

Differentiable Cluster Graph Neural Network
by: Dong, Yanfei, et al.
Published: (2024)

Permutation-Invariant Representation Learning for Robust and Privacy-Preserving Feature Selection
by: Liu, Rui, et al.
Published: (2025)

Invariant Representations with Stochastically Quantized Neural Networks
by: Cerrato, Mattia, et al.
Published: (2022)

COD: Learning Conditional Invariant Representation for Domain Adaptation Regression
by: Yang, Hao-Ran, et al.
Published: (2024)

Hierarchical Frequency-Decomposition Graph Neural Networks for Road Network Representation Learning
by: Ma, Jingtian, et al.
Published: (2025)

Learning Time-Scale Invariant Population-Level Neural Representations
by: Patel, Eshani, et al.
Published: (2025)

When Invariant Representation Learning Meets Label Shift: Insufficiency and Theoretical Insights
by: Luo, You-Wei, et al.
Published: (2024)

Permutation-Invariant Graph Partitioning:How Graph Neural Networks Capture Structural Interactions?
by: Hevapathige, Asela, et al.
Published: (2023)

TANGNN: a Concise, Scalable and Effective Graph Neural Networks with Top-m Attention Mechanism for Graph Representation Learning
by: E, Jiawei, et al.
Published: (2024)

Inductive Graph Representation Learning with Quantum Graph Neural Networks
by: Faria, Arthur M., et al.
Published: (2025)

Towards OOD Generalization in Dynamic Graphs via Causal Invariant Learning
by: Zhang, Xinxun, et al.
Published: (2026)

LSEnet: Lorentz Structural Entropy Neural Network for Deep Graph Clustering
by: Sun, Li, et al.
Published: (2024)

Adversarial Training for Graph Neural Networks via Graph Subspace Energy Optimization
by: Liu, Ganlin, et al.
Published: (2024)

Asymmetric Learning for Spectral Graph Neural Networks
by: Liu, Fangbing, et al.
Published: (2024)

Dynamic User Interest Augmentation via Stream Clustering and Memory Networks in Large-Scale Recommender Systems
by: Liu, Peng, et al.
Published: (2024)

Node Identifiers: Compact, Discrete Representations for Efficient Graph Learning
by: Luo, Yuankai, et al.
Published: (2024)

GLANCE: Graph Logic Attention Network with Cluster Enhancement for Heterophilous Graph Representation Learning
by: Sun, Zhongtian, et al.
Published: (2025)

Advancing Biomedicine with Graph Representation Learning: Recent Progress, Challenges, and Future Directions
by: Li, Fang, et al.
Published: (2023)

Globally Interpretable Graph Learning via Distribution Matching
by: Nian, Yi, et al.
Published: (2023)