:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zhang, Jing, Jiang, Xiaoqian, Xie, Yingjie, Zhou, Cangqi
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2407.00708
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

AS-GCL: Asymmetric Spectral Augmentation on Graph Contrastive Learning
by: Liu, Ruyue, et al.
Published: (2025)

FairACE: Achieving Degree Fairness in Graph Neural Networks via Contrastive and Adversarial Group-Balanced Training
by: Liu, Jiaxin, et al.
Published: (2025)

Rethinking Spectral Augmentation for Contrast-based Graph Self-Supervised Learning
by: Jian, Xiangru, et al.
Published: (2024)

Unifying Graph Contrastive Learning via Graph Message Augmentation
by: Zhang, Ziyan, et al.
Published: (2024)

Edge Contrastive Learning: An Augmentation-Free Graph Contrastive Learning Model
by: Li, Yujun, et al.
Published: (2024)

Jointly Learning Representations for Map Entities via Heterogeneous Graph Contrastive Learning
by: Jiang, Jiawei, et al.
Published: (2024)

Graph Contrastive Learning via Spectral Graph Alignment
by: Nguyen, Manh
Published: (2025)

Incorporating Attributes and Multi-Scale Structures for Heterogeneous Graph Contrastive Learning
by: Jiang, Ruobing, et al.
Published: (2025)

Disjoint Contrastive Regression Learning for Multi-Sourced Annotations
by: Ruan, Xiaoqian, et al.
Published: (2021)

Heterogeneous Contrastive Learning for Foundation Models and Beyond
by: Zheng, Lecheng, et al.
Published: (2024)

Heterogeneous Graph Contrastive Learning with Meta-path Contexts and Adaptively Weighted Negative Samples
by: Yu, Jianxiang, et al.
Published: (2022)

Contrastive Learning Is Spectral Clustering On Similarity Graph
by: Tan, Zhiquan, et al.
Published: (2023)

Homophily-aware Heterogeneous Graph Contrastive Learning
by: Wang, Haosen, et al.
Published: (2025)

Simple and Asymmetric Graph Contrastive Learning without Augmentations
by: Xiao, Teng, et al.
Published: (2023)

CGCL: Collaborative Graph Contrastive Learning without Handcrafted Graph Data Augmentations
by: Zhang, Tianyu, et al.
Published: (2021)

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

LOHA: Direct Graph Spectral Contrastive Learning Between Low-pass and High-pass Views
by: Zou, Ziyun, et al.
Published: (2025)

Generative-Contrastive Heterogeneous Graph Neural Network
by: Wang, Yu, et al.
Published: (2024)

Variational Graph Contrastive Learning
by: Xie, Shifeng, et al.
Published: (2024)

Adversarial Curriculum Graph Contrastive Learning with Pair-wise Augmentation
by: Zhao, Xinjian, et al.
Published: (2024)

Rethinking Graph Domain Adaptation: A Spectral Contrastive Perspective
by: Zhang, Haoyu, et al.
Published: (2025)

CHAT: Beyond Contrastive Graph Transformer for Link Prediction in Heterogeneous Networks
by: Zhang, Shengming, et al.
Published: (2025)

ARIEL: Adversarial Graph Contrastive Learning
by: Feng, Shengyu, et al.
Published: (2022)

Learning Robust Heterogeneous Graph Representations via Contrastive-Reconstruction under Sparse Semantics
by: Lin, Di, et al.
Published: (2025)

Fractal Graph Contrastive Learning
by: Li, Nero Z., et al.
Published: (2025)

Learning Feature Encoder with Synthetic Anomalies for Weakly Supervised Graph Anomaly Detection
by: Zhou, Yingjie, et al.
Published: (2026)

A Transformer-Based Deep Learning Approach for Fairly Predicting Post-Liver Transplant Risk Factors
by: Li, Can, et al.
Published: (2023)

Semi-supervised Domain Adaptation on Graphs with Contrastive Learning and Minimax Entropy
by: Xiao, Jiaren, et al.
Published: (2023)

Masked Graph Autoencoders with Contrastive Augmentation for Spatially Resolved Transcriptomics Data
by: Fang, Donghai, et al.
Published: (2024)

Spectral-Aware Augmentation for Enhanced Graph Representation Learning
by: Yang, Kaiqi, et al.
Published: (2023)

LAC: Graph Contrastive Learning with Learnable Augmentation in Continuous Space
by: Lin, Zhenyu, et al.
Published: (2024)

Multimodal Contrastive Representation Learning in Augmented Biomedical Knowledge Graphs
by: Dang, Tien, et al.
Published: (2025)

Graph Data Augmentation with Contrastive Learning on Covariate Distribution Shift
by: Zeng, Fanlong, et al.
Published: (2025)

Community-Invariant Graph Contrastive Learning
by: Tan, Shiyin, et al.
Published: (2024)

ASPECT: Node-Level Adaptive Spectral Fusion for Graph Contrastive Learning
by: Li, Zhuolong, et al.
Published: (2026)

SOLA-GCL: Subgraph-Oriented Learnable Augmentation Method for Graph Contrastive Learning
by: Peng, Tianhao, et al.
Published: (2025)

NoiseHGNN: Synthesized Similarity Graph-Based Neural Network For Noised Heterogeneous Graph Representation Learning
by: Zhang, Xiong, et al.
Published: (2024)

Contrastive Multi-Task Learning with Solvent-Aware Augmentation for Drug Discovery
by: Lan, Jing, et al.
Published: (2025)

An Augmentation Overlap Theory of Contrastive Learning
by: Zhang, Qi, et al.
Published: (2025)

CoSD: Collaborative Stance Detection with Contrastive Heterogeneous Topic Graph Learning
by: Cheng, Yinghan, et al.
Published: (2024)