Saved in:
| Main Authors: | Chen, Jie, Mao, Hua, Liu, Chuanbin, Wang, Zhu, Peng, Xi |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2411.15206 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Cross-View Graph Consistency Learning for Invariant Graph Representations
by: Chen, Jie, et al.
Published: (2023)
by: Chen, Jie, et al.
Published: (2023)
A Unified Invariant Learning Framework for Graph Classification
by: Sui, Yongduo, et al.
Published: (2025)
by: Sui, Yongduo, et al.
Published: (2025)
Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization
by: Mao, Wenyu, et al.
Published: (2024)
by: Mao, Wenyu, et al.
Published: (2024)
Graph Classification via Reference Distribution Learning: Theory and Practice
by: Wang, Zixiao, et al.
Published: (2024)
by: Wang, Zixiao, et al.
Published: (2024)
Brain Network Classification Based on Graph Contrastive Learning and Graph Transformer
by: Zhu, ZhiTeng, et al.
Published: (2025)
by: Zhu, ZhiTeng, et al.
Published: (2025)
GraphRCG: Self-Conditioned Graph Generation
by: Wang, Song, et al.
Published: (2024)
by: Wang, Song, et al.
Published: (2024)
Generalizing Graph Neural Networks on Out-Of-Distribution Graphs
by: Fan, Shaohua, et al.
Published: (2021)
by: Fan, Shaohua, et al.
Published: (2021)
Weighted Graph Structure Learning with Attention Denoising for Node Classification
by: Wang, Tingting, et al.
Published: (2025)
by: Wang, Tingting, et al.
Published: (2025)
Score-based Conditional Out-of-Distribution Augmentation for Graph Covariate Shift
by: Wang, Bohan, et al.
Published: (2024)
by: Wang, Bohan, et al.
Published: (2024)
A Transformer-Based Conditional GAN with Multiple Instance Learning for UAV Signal Detection and Classification
by: Liu, Haochen, et al.
Published: (2025)
by: Liu, Haochen, et al.
Published: (2025)
Learning From Graph-Structured Data: Addressing Design Issues and Exploring Practical Applications in Graph Representation Learning
by: Hua, Chenqing
Published: (2024)
by: Hua, Chenqing
Published: (2024)
Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts
by: Zhang, Zeyang, et al.
Published: (2024)
by: Zhang, Zeyang, et al.
Published: (2024)
Prompt-Driven Continual Graph Learning
by: Wang, Qi, et al.
Published: (2025)
by: Wang, Qi, et al.
Published: (2025)
Pareto Continual Learning: Preference-Conditioned Learning and Adaption for Dynamic Stability-Plasticity Trade-off
by: Lai, Song, et al.
Published: (2025)
by: Lai, Song, et al.
Published: (2025)
CoCo: A Coupled Contrastive Framework for Unsupervised Domain Adaptive Graph Classification
by: Yin, Nan, et al.
Published: (2023)
by: Yin, Nan, et al.
Published: (2023)
Learning to Explore: Policy-Guided Outlier Synthesis for Graph Out-of-Distribution Detection
by: Sun, Li, et al.
Published: (2026)
by: Sun, Li, et al.
Published: (2026)
Few-Shot Causal Representation Learning for Out-of-Distribution Generalization on Heterogeneous Graphs
by: Ding, Pengfei, et al.
Published: (2024)
by: Ding, Pengfei, et al.
Published: (2024)
BET: Explaining Deep Reinforcement Learning through The Error-Prone Decisions
by: Liu, Xiao, et al.
Published: (2024)
by: Liu, Xiao, et al.
Published: (2024)
Goal Exploration via Adaptive Skill Distribution for Goal-Conditioned Reinforcement Learning
by: Wu, Lisheng, et al.
Published: (2024)
by: Wu, Lisheng, et al.
Published: (2024)
Graph Propagation Transformer for Graph Representation Learning
by: Chen, Zhe, et al.
Published: (2023)
by: Chen, Zhe, et al.
Published: (2023)
GraphCLIP: Enhancing Transferability in Graph Foundation Models for Text-Attributed Graphs
by: Zhu, Yun, et al.
Published: (2024)
by: Zhu, Yun, et al.
Published: (2024)
Markov Process-Based Graph Convolutional Networks for Entity Classification in Knowledge Graphs
by: Mäkelburg, Johannes, et al.
Published: (2024)
by: Mäkelburg, Johannes, et al.
Published: (2024)
Exploratory Machine Learning with Unknown Unknowns
by: Zhao, Peng, et al.
Published: (2020)
by: Zhao, Peng, et al.
Published: (2020)
Label-free Node Classification on Graphs with Large Language Models (LLMS)
by: Chen, Zhikai, et al.
Published: (2023)
by: Chen, Zhikai, et al.
Published: (2023)
Graphs Generalization under Distribution Shifts
by: Tian, Qin, et al.
Published: (2024)
by: Tian, Qin, et al.
Published: (2024)
A Binary Classification Social Network Dataset for Graph Machine Learning
by: Ali, Adnan, et al.
Published: (2025)
by: Ali, Adnan, et al.
Published: (2025)
Generative Risk Minimization for Out-of-Distribution Generalization on Graphs
by: Wang, Song, et al.
Published: (2025)
by: Wang, Song, et al.
Published: (2025)
Cooperative Classification and Rationalization for Graph Generalization
by: Yue, Linan, et al.
Published: (2024)
by: Yue, Linan, et al.
Published: (2024)
Foundations and Frontiers of Graph Learning Theory
by: Huang, Yu, et al.
Published: (2024)
by: Huang, Yu, et al.
Published: (2024)
AKBR: Learning Adaptive Kernel-based Representations for Graph Classification
by: Qian, Feifei, et al.
Published: (2024)
by: Qian, Feifei, et al.
Published: (2024)
Discretizing Continuous Action Space with Unimodal Probability Distributions for On-Policy Reinforcement Learning
by: Zhu, Yuanyang, et al.
Published: (2024)
by: Zhu, Yuanyang, et al.
Published: (2024)
Graph Learning with Distributional Edge Layouts
by: Zhao, Xinjian, et al.
Published: (2024)
by: Zhao, Xinjian, et al.
Published: (2024)
DisenSemi: Semi-supervised Graph Classification via Disentangled Representation Learning
by: Wang, Yifan, et al.
Published: (2024)
by: Wang, Yifan, et al.
Published: (2024)
Adversarial Preference Learning for Robust LLM Alignment
by: Wang, Yuanfu, et al.
Published: (2025)
by: Wang, Yuanfu, et al.
Published: (2025)
Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs
by: Chen, Zhikai, et al.
Published: (2023)
by: Chen, Zhikai, et al.
Published: (2023)
DBGL: Decay-aware Bipartite Graph Learning for Irregular Medical Time Series Classification
by: Chen, Jian, et al.
Published: (2026)
by: Chen, Jian, et al.
Published: (2026)
Structure-Aware Distributed Backdoor Attacks in Federated Learning
by: Jian, Wang, et al.
Published: (2026)
by: Jian, Wang, et al.
Published: (2026)
DeNoise: Learning Robust Graph Representations for Unsupervised Graph-Level Anomaly Detection
by: Chen, Qingfeng, et al.
Published: (2025)
by: Chen, Qingfeng, et al.
Published: (2025)
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)
GSTBench: A Benchmark Study on the Transferability of Graph Self-Supervised Learning
by: Song, Yu, et al.
Published: (2025)
by: Song, Yu, et al.
Published: (2025)
Similar Items
-
Cross-View Graph Consistency Learning for Invariant Graph Representations
by: Chen, Jie, et al.
Published: (2023) -
A Unified Invariant Learning Framework for Graph Classification
by: Sui, Yongduo, et al.
Published: (2025) -
Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization
by: Mao, Wenyu, et al.
Published: (2024) -
Graph Classification via Reference Distribution Learning: Theory and Practice
by: Wang, Zixiao, et al.
Published: (2024) -
Brain Network Classification Based on Graph Contrastive Learning and Graph Transformer
by: Zhu, ZhiTeng, et al.
Published: (2025)