:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Djima, Karamatou Yacoubou, Yim, Ka Man
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Social and Information Networks
Online Access:	https://arxiv.org/abs/2503.09660
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

The Expressive Power of Graph Neural Networks: A Survey
by: Zhang, Bingxu, et al.
Published: (2023)

Accurate Link Prediction for Edge-Incomplete Graphs via PU Learning
by: Kim, Junghun, et al.
Published: (2024)

Explaining the Power of Topological Data Analysis in Graph Machine Learning
by: Taiwo, Funmilola Mary, et al.
Published: (2024)

Revisiting Graph-Based Fraud Detection in Sight of Heterophily and Spectrum
by: Xu, Fan, et al.
Published: (2023)

Improving Expressive Power of Spectral Graph Neural Networks with Eigenvalue Correction
by: Lu, Kangkang, et al.
Published: (2024)

Graph Learning under Distribution Shifts: A Comprehensive Survey on Domain Adaptation, Out-of-distribution, and Continual Learning
by: Wu, Man, et al.
Published: (2024)

Infinite-Horizon Graph Filters: Leveraging Power Series to Enhance Sparse Information Aggregation
by: Zhang, Ruizhe, et al.
Published: (2024)

Learning Scalable Structural Representations for Link Prediction with Bloom Signatures
by: Zhang, Tianyi, et al.
Published: (2023)

Hybrid Graph: A Unified Graph Representation with Datasets and Benchmarks for Complex Graphs
by: Li, Zehui, et al.
Published: (2023)

Quantile-Based Randomized Kaczmarz for Corrupted Tensor Linear Systems
by: Castillo, Alejandra, et al.
Published: (2025)

On the Power of Graph Neural Networks and Feature Augmentation Strategies to Classify Social Networks
by: Guettala, Walid, et al.
Published: (2024)

Incorporating Heterophily into Graph Neural Networks for Graph Classification
by: Yang, Jiayi, et al.
Published: (2022)

Unifying Generation and Prediction on Graphs with Latent Graph Diffusion
by: Zhou, Cai, et al.
Published: (2024)

GravityGraphSAGE: Link Prediction in Directed Attributed Graphs
by: Porcedda, Riccardo, et al.
Published: (2026)

Dynamic Graph with Similarity-Aware Attention Graph Neural Network for Recommender Systems
by: Senapati, Aadarsh, et al.
Published: (2026)

A Unified Graph Selective Prompt Learning for Graph Neural Networks
by: Jiang, Bo, et al.
Published: (2024)

What Is Missing In Homophily? Disentangling Graph Homophily For Graph Neural Networks
by: Zheng, Yilun, et al.
Published: (2024)

GraphSB: Boosting Imbalanced Node Classification on Graphs through Structural Balance
by: Zhu, Chaofan, et al.
Published: (2025)

Homophily-Related: Adaptive Hybrid Graph Filter for Multi-View Graph Clustering
by: Wen, Zichen, et al.
Published: (2024)

GraphMU: Repairing Robustness of Graph Neural Networks via Machine Unlearning
by: Wu, Tao, et al.
Published: (2024)

Generalizing Graph Transformers Across Diverse Graphs and Tasks via Pre-training
by: He, Yufei, et al.
Published: (2024)

Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective
by: Lee, Soo Yong, et al.
Published: (2024)

Deep-Graph-Sprints: Accelerated Representation Learning in Continuous-Time Dynamic Graphs
by: Eddin, Ahmad Naser, et al.
Published: (2024)

The Graph-Embedded Hazard Model (GEHM): Stochastic Network Survival Dynamics on Economic Graphs
by: Vallarino, Diego
Published: (2025)

Using Time-Aware Graph Neural Networks to Predict Temporal Centralities in Dynamic Graphs
by: Heeg, Franziska, et al.
Published: (2023)

Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure
by: Sato, Ryoma
Published: (2023)

GraphSL: An Open-Source Library for Graph Source Localization Approaches and Benchmark Datasets
by: Wang, Junxiang, et al.
Published: (2024)

Neural Graph Generator: Feature-Conditioned Graph Generation using Latent Diffusion Models
by: Evdaimon, Iakovos, et al.
Published: (2024)

HeteGraph-Mamba: Heterogeneous Graph Learning via Selective State Space Model
by: Pan, Zhenyu, et al.
Published: (2024)

TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs
by: Gastinger, Julia, et al.
Published: (2024)

Community-Centric Graph Unlearning
by: Li, Yi, et al.
Published: (2024)

Fine-grained Graph Rationalization
by: Xu, Zhe, et al.
Published: (2023)

Temporal Graph Analysis with TGX
by: Shirzadkhani, Razieh, et al.
Published: (2024)

Neural Acceleration for Graph Partitioning
by: Booth, Joshua Dennis, et al.
Published: (2026)

InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections
by: Qin, Meng, et al.
Published: (2025)

Graph Structure Prompt Learning: A Novel Methodology to Improve Performance of Graph Neural Networks
by: Huang, Zhenhua, et al.
Published: (2024)

LangGFM: A Large Language Model Alone Can be a Powerful Graph Foundation Model
by: Lin, Tianqianjin, et al.
Published: (2024)

Mitigating Bias in Graph Hyperdimensional Computing
by: Liu, Yezi, et al.
Published: (2025)

Unlearning Algorithmic Biases over Graphs
by: Kose, O. Deniz, et al.
Published: (2025)

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