:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Shi, Zhihao, Wang, Jie, Zhuang, Zhiwei, Liang, Xize, Li, Bin, Wu, Feng
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2502.19693
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

FlowX: Towards Explainable Graph Neural Networks via Message Flows
by: Gui, Shurui, et al.
Published: (2022)

ROPO: Robust Preference Optimization for Large Language Models
by: Liang, Xize, et al.
Published: (2024)

Towards Scalable and Deep Graph Neural Networks via Noise Masking
by: Liang, Yuxuan, et al.
Published: (2024)

Heterophilic Graph Neural Networks Optimization with Causal Message-passing
by: Wang, Botao, et al.
Published: (2024)

LMC: Fast Training of GNNs via Subgraph Sampling with Provable Convergence
by: Shi, Zhihao, et al.
Published: (2023)

FSX: Message Flow Sensitivity Enhanced Structural Explainer for Graph Neural Networks
by: Feng, Bizu, et al.
Published: (2026)

ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks
by: Wang, Yuelin, et al.
Published: (2022)

Transfer learning in Scalable Graph Neural Network for Improved Physical Simulation
by: Shen, Siqi, et al.
Published: (2025)

LPS-GNN : Deploying Graph Neural Networks on Graphs with 100-Billion Edges
by: Cheng, Xu, et al.
Published: (2025)

Label Deconvolution for Node Representation Learning on Large-scale Attributed Graphs against Learning Bias
by: Shi, Zhihao, et al.
Published: (2023)

How Explanations Leak the Decision Logic: Stealing Graph Neural Networks via Explanation Alignment
by: Ma, Bin, et al.
Published: (2025)

FairSample: Training Fair and Accurate Graph Convolutional Neural Networks Efficiently
by: Cong, Zicun, et al.
Published: (2024)

Boolean Product Graph Neural Networks
by: Wang, Ziyan, et al.
Published: (2024)

GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks
by: Younesian, Taraneh, et al.
Published: (2023)

Enhancing the Resilience of Graph Neural Networks to Topological Perturbations in Sparse Graphs
by: He, Shuqi, et al.
Published: (2024)

SIG: Efficient Self-Interpretable Graph Neural Network for Continuous-time Dynamic Graphs
by: Fang, Lanting, et al.
Published: (2024)

Unlearning Inversion Attacks for Graph Neural Networks
by: Zhang, Jiahao, et al.
Published: (2025)

A Diffusion-Contrastive Graph Neural Network with Virtual Nodes for Wind Nowcasting in Unobserved Regions
by: Shi, Jie, et al.
Published: (2026)

SF-GNN: Self Filter for Message Lossless Propagation in Deep Graph Neural Network
by: Zhu, Yushan, et al.
Published: (2024)

Handling Distribution Shifts on Graphs: An Invariance Perspective
by: Wu, Qitian, et al.
Published: (2022)

SwinGNN: Rethinking Permutation Invariance in Diffusion Models for Graph Generation
by: Yan, Qi, et al.
Published: (2023)

ADEdgeDrop: Adversarial Edge Dropping for Robust Graph Neural Networks
by: Chen, Zhaoliang, et al.
Published: (2024)

SpecReason: Fast and Accurate Inference-Time Compute via Speculative Reasoning
by: Pan, Rui, et al.
Published: (2025)

GRExplainer: A Universal Explanation Method for Temporal Graph Neural Networks
by: Li, Xuyan, et al.
Published: (2025)

Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity
by: Ding, Mucong, et al.
Published: (2024)

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

Deeper Insights into Deep Graph Convolutional Networks: Stability and Generalization
by: Yang, Guangrui, et al.
Published: (2024)

MLGIB: Multi-Label Graph Information Bottleneck for Expressive and Robust Message Passing
by: Wu, Chaokai, et al.
Published: (2026)

Accelerating Data Generation for Neural Operators via Krylov Subspace Recycling
by: Wang, Hong, et al.
Published: (2024)

Quasi-Framelets: Robust Graph Neural Networks via Adaptive Framelet Convolution
by: Yang, Mengxi, et al.
Published: (2022)

BeMap: Balanced Message Passing for Fair Graph Neural Network
by: Lin, Xiao, et al.
Published: (2023)

ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks
by: You, Haoran, et al.
Published: (2022)

Non-Euclidean Spatial Graph Neural Network
by: Zhang, Zheng, et al.
Published: (2023)

GraphFramEx: Towards Systematic Evaluation of Explainability Methods for Graph Neural Networks
by: Amara, Kenza, et al.
Published: (2022)

Unsupervised Disentanglement of Content and Style via Variance-Invariance Constraints
by: Wu, Yuxuan, et al.
Published: (2024)

Discovering the Representation Bottleneck of Graph Neural Networks
by: Wu, Fang, et al.
Published: (2022)

Contrastive Dual-Interaction Graph Neural Network for Molecular Property Prediction
by: Zhao, Zexing, et al.
Published: (2024)

Causal Graph Learning via Distributional Invariance of Cause-Effect Relationship
by: Nguyen, Nang Hung, et al.
Published: (2026)

Beyond Message Passing: Neural Graph Pattern Machine
by: Wang, Zehong, et al.
Published: (2025)

Faithful and Accurate Self-Attention Attribution for Message Passing Neural Networks via the Computation Tree Viewpoint
by: Shin, Yong-Min, et al.
Published: (2024)