Revisiting Graph Autoencoders as Implicit Contrastive Learners
Fuente:
arXiv
Saved in:
| Main Authors: | Li, Jintang, Wu, Ruofan, Zhu, Yuchang, Zhang, Huizhe, Zhu, Zulun, Chen, Liang |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Are Large Language Models In-Context Graph Learners?
by: Li, Jintang, et al.
Published: (2025)
by: Li, Jintang, et al.
Published: (2025)
A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks
by: Li, Jintang, et al.
Published: (2023)
by: Li, Jintang, et al.
Published: (2023)
Oversmoothing: A Nightmare for Graph Contrastive Learning?
by: Li, Jintang, et al.
Published: (2023)
by: Li, Jintang, et al.
Published: (2023)
SGNNBench: A Holistic Evaluation of Spiking Graph Neural Network on Large-scale Graph
by: Zhang, Huizhe, et al.
Published: (2025)
by: Zhang, Huizhe, et al.
Published: (2025)
SGHormer: An Energy-Saving Graph Transformer Driven by Spikes
by: Zhang, Huizhe, et al.
Published: (2024)
by: Zhang, Huizhe, et al.
Published: (2024)
SaGIF: Improving Individual Fairness in Graph Neural Networks via Similarity Encoding
by: Zhu, Yuchang, et al.
Published: (2025)
by: Zhu, Yuchang, et al.
Published: (2025)
Revisiting Modularity Maximization for Graph Clustering: A Contrastive Learning Perspective
by: Liu, Yunfei, et al.
Published: (2024)
by: Liu, Yunfei, et al.
Published: (2024)
GT-SNT: A Linear-Time Transformer for Large-Scale Graphs via Spiking Node Tokenization
by: Zhang, Huizhe, et al.
Published: (2025)
by: Zhang, Huizhe, et al.
Published: (2025)
State Space Models on Temporal Graphs: A First-Principles Study
by: Li, Jintang, et al.
Published: (2024)
by: Li, Jintang, et al.
Published: (2024)
Fair Graph Representation Learning via Sensitive Attribute Disentanglement
by: Zhu, Yuchang, et al.
Published: (2024)
by: Zhu, Yuchang, et al.
Published: (2024)
Measuring Diversity in Synthetic Datasets
by: Zhu, Yuchang, et al.
Published: (2025)
by: Zhu, Yuchang, et al.
Published: (2025)
Masked Graph Autoencoders with Contrastive Augmentation for Spatially Resolved Transcriptomics Data
by: Fang, Donghai, et al.
Published: (2024)
by: Fang, Donghai, et al.
Published: (2024)
One Fits All: Learning Fair Graph Neural Networks for Various Sensitive Attributes
by: Zhu, Yuchang, et al.
Published: (2024)
by: Zhu, Yuchang, et al.
Published: (2024)
A Comprehensive Benchmark on Spectral GNNs: The Impact on Efficiency, Memory, and Effectiveness
by: Liao, Ningyi, et al.
Published: (2024)
by: Liao, Ningyi, et al.
Published: (2024)
E-CGL: An Efficient Continual Graph Learner
by: Guo, Jianhao, et al.
Published: (2024)
by: Guo, Jianhao, et al.
Published: (2024)
Pre-Training Graph Contrastive Masked Autoencoders are Strong Distillers for EEG
by: Wei, Xinxu, et al.
Published: (2024)
by: Wei, Xinxu, 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)
Coden: Efficient Temporal Graph Neural Networks for Continuous Prediction
by: Zhu, Zulun, et al.
Published: (2026)
by: Zhu, Zulun, et al.
Published: (2026)
Dual-Kernel Graph Community Contrastive Learning
by: Chen, Xiang, et al.
Published: (2025)
by: Chen, Xiang, et al.
Published: (2025)
Graph Autoencoder for Process Monitoring
by: Zhang, Xiangrui
Published: (2026)
by: Zhang, Xiangrui
Published: (2026)
Uncovering Capabilities of Model Pruning in Graph Contrastive Learning
by: Wu, Junran, et al.
Published: (2024)
by: Wu, Junran, et al.
Published: (2024)
Understanding and Mitigating Hyperbolic Dimensional Collapse in Graph Contrastive Learning
by: Zhang, Yifei, et al.
Published: (2023)
by: Zhang, Yifei, et al.
Published: (2023)
Sparse Autoencoders, Again?
by: Lu, Yin, et al.
Published: (2025)
by: Lu, Yin, et al.
Published: (2025)
Tensor-Fused Multi-View Graph Contrastive Learning
by: Wu, Yujia, et al.
Published: (2024)
by: Wu, Yujia, et al.
Published: (2024)
Graph-Regularized Sparse Autoencoders for LLM Safety Steering
by: Yeon, Jehyeok, et al.
Published: (2025)
by: Yeon, Jehyeok, et al.
Published: (2025)
Croppable Knowledge Graph Embedding
by: Zhu, Yushan, et al.
Published: (2024)
by: Zhu, Yushan, et al.
Published: (2024)
GRAIN: Multi-Granular and Implicit Information Aggregation Graph Neural Network for Heterophilous Graphs
by: Zhao, Songwei, et al.
Published: (2025)
by: Zhao, Songwei, et al.
Published: (2025)
IMPA-HGAE:Intra-Meta-Path Augmented Heterogeneous Graph Autoencoder
by: Lin, Di, et al.
Published: (2025)
by: Lin, Di, et al.
Published: (2025)
UGMAE: A Unified Framework for Graph Masked Autoencoders
by: Tian, Yijun, et al.
Published: (2024)
by: Tian, Yijun, et al.
Published: (2024)
ISEP: Implicit Support Expansion for Offline Reinforcement Learning via Stochastic Policy Optimization
by: Chen, Yifei, et al.
Published: (2026)
by: Chen, Yifei, et al.
Published: (2026)
Adversarial Curriculum Graph Contrastive Learning with Pair-wise Augmentation
by: Zhao, Xinjian, et al.
Published: (2024)
by: Zhao, Xinjian, et al.
Published: (2024)
LocalGCL: Local-aware Contrastive Learning for Graphs
by: Jiang, Haojun, et al.
Published: (2024)
by: Jiang, Haojun, et al.
Published: (2024)
Revisiting Data Attribution for Influence Functions
by: Zhu, Hongbo, et al.
Published: (2025)
by: Zhu, Hongbo, et al.
Published: (2025)
Topology Reorganized Graph Contrastive Learning with Mitigating Semantic Drift
by: Zhang, Jiaqiang, et al.
Published: (2024)
by: Zhang, Jiaqiang, et al.
Published: (2024)
Deep Contrastive Graph Learning with Clustering-Oriented Guidance
by: Chen, Mulin, et al.
Published: (2024)
by: Chen, Mulin, et al.
Published: (2024)
Robust Unsupervised Fault Diagnosis For High-Dimensional Nonlinear Noisy Data
by: Zhao, Dandan, et al.
Published: (2025)
by: Zhao, Dandan, et al.
Published: (2025)
Agentic-VLA: Efficient Online Adaptation for Vision-Language-Action Models
by: Jin, Ruofan, et al.
Published: (2026)
by: Jin, Ruofan, et al.
Published: (2026)
Graph is a Natural Regularization: Revisiting Vector Quantization for Graph Representation Learning
by: Zhai, Zian, et al.
Published: (2025)
by: Zhai, Zian, et al.
Published: (2025)
Generalized Graph Transformer Variational Autoencoder
by: Karki, Siddhant
Published: (2025)
by: Karki, Siddhant
Published: (2025)
DP-DCAN: Differentially Private Deep Contrastive Autoencoder Network for Single-cell Clustering
by: Li, Huifa, et al.
Published: (2023)
by: Li, Huifa, et al.
Published: (2023)
Similar Items
-
Are Large Language Models In-Context Graph Learners?
by: Li, Jintang, et al.
Published: (2025) -
A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks
by: Li, Jintang, et al.
Published: (2023) -
Oversmoothing: A Nightmare for Graph Contrastive Learning?
by: Li, Jintang, et al.
Published: (2023) -
SGNNBench: A Holistic Evaluation of Spiking Graph Neural Network on Large-scale Graph
by: Zhang, Huizhe, et al.
Published: (2025) -
SGHormer: An Energy-Saving Graph Transformer Driven by Spikes
by: Zhang, Huizhe, et al.
Published: (2024)