Cover Image

SAGMAN: Stability Analysis of Graph Neural Networks on the Manifolds

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Cheng, Wuxinlin, Deng, Chenhui, Aghdaei, Ali, Zhang, Zhiru, Feng, Zhuo
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

SGM-PINN: Sampling Graphical Models for Faster Training of Physics-Informed Neural Networks
by: Anticev, John, et al.
Published: (2024)

SALMAN: Stability Analysis of Language Models Through the Maps Between Graph-based Manifolds
by: Cheng, Wuxinlin, et al.
Published: (2025)

Polynormer: Polynomial-Expressive Graph Transformer in Linear Time
by: Deng, Chenhui, et al.
Published: (2024)

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

inGRASS: Incremental Graph Spectral Sparsification via Low-Resistance-Diameter Decomposition
by: Aghdaei, Ali, et al.
Published: (2024)

Commute Graph Neural Networks
by: Zhuo, Wei, et al.
Published: (2024)

Graph Neural Networks with Feature and Structure Aware Random Walk
by: Zhuo, Wei, et al.
Published: (2021)

Graphs Unveiled: Graph Neural Networks and Graph Generation
by: Kovács, László, et al.
Published: (2024)

Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs
by: Yue, Zichao, et al.
Published: (2025)

Can we ease the Injectivity Bottleneck on Lorentzian Manifolds for Graph Neural Networks?
by: Srinivasan, Srinitish, et al.
Published: (2025)

mHC-GNN: Manifold-Constrained Hyper-Connections for Graph Neural Networks
by: Mishra, Subhankar
Published: (2026)

Deep Manifold Part 1: Anatomy of Neural Network Manifold
by: Ma, Max Y., et al.
Published: (2024)

A Spectral Framework for Evaluating Geodesic Distances Between Graphs
by: Shuvo, Soumen Sikder, et al.
Published: (2024)

Leveraging Manifold Embeddings for Enhanced Graph Transformer Representations and Learning
by: Jyothish, Ankit, et al.
Published: (2025)

Graph Attention Networks Unleashed: A Fast and Explainable Vulnerability Assessment Framework for Microgrids
by: Liu, Wei, et al.
Published: (2025)

Differentiable Cluster Graph Neural Network
by: Dong, Yanfei, et al.
Published: (2024)

Deep Manifold Part 2: Neural Network Mathematics
by: Ma, Max Y., et al.
Published: (2025)

Factor Graph-based Interpretable Neural Networks
by: Li, Yicong, et al.
Published: (2025)

Conformalized Link Prediction on Graph Neural Networks
by: Zhao, Tianyi, et al.
Published: (2024)

Residual Reweighted Conformal Prediction for Graph Neural Networks
by: Zhang, Zheng, et al.
Published: (2025)

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

FUGNN: Harmonizing Fairness and Utility in Graph Neural Networks
by: Luo, Renqiang, et al.
Published: (2024)

Graph Neural Networks for Learning Equivariant Representations of Neural Networks
by: Kofinas, Miltiadis, et al.
Published: (2024)

SHyPar: A Spectral Coarsening Approach to Hypergraph Partitioning
by: Sajadinia, Hamed, et al.
Published: (2024)

GraphTOP: Graph Topology-Oriented Prompting for Graph Neural Networks
by: Fu, Xingbo, et al.
Published: (2025)

Sparse Decomposition of Graph Neural Networks
by: Hu, Yaochen, et al.
Published: (2024)

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

Orientation-Aware Graph Neural Networks for Protein Structure Representation Learning
by: Li, Jiahan, et al.
Published: (2022)

Graph Neural Networks for Heart Failure Prediction on an EHR-Based Patient Similarity Graph
by: Boll, Heloisa Oss, et al.
Published: (2024)

Online Adversarial Knowledge Distillation for Graph Neural Networks
by: Wang, Can, et al.
Published: (2021)

QuadraNet V2: Efficient and Sustainable Training of High-Order Neural Networks with Quadratic Adaptation
by: Xu, Chenhui, et al.
Published: (2024)

ManifoldFormer: Geometric Deep Learning for Neural Dynamics on Riemannian Manifolds
by: Fu, Yihang, et al.
Published: (2025)

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

Rayleigh Quotient Graph Neural Networks for Graph-level Anomaly Detection
by: Dong, Xiangyu, et al.
Published: (2023)

Framework GNN-AID: Graph Neural Network Analysis Interpretation and Defense
by: Lukyanov, Kirill, et al.
Published: (2025)

Accurate and Scalable Graph Neural Networks via Message Invariance
by: Shi, Zhihao, et al.
Published: (2025)

Large Language Models Meet Graph Neural Networks for Text-Numeric Graph Reasoning
by: Song, Haoran, et al.
Published: (2025)

Relating-Up: Advancing Graph Neural Networks through Inter-Graph Relationships
by: Zou, Qi, et al.
Published: (2024)

Unifying Adversarial Perturbation for Graph Neural Networks
by: Yang, Jinluan, et al.
Published: (2025)

Universal Prompt Tuning for Graph Neural Networks
by: Fang, Taoran, et al.
Published: (2022)