Image de couverture de livre

Graph Attention Network for Node Regression on Random Geometric Graphs with Erdős--Rényi contamination

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Laha, Somak, Liu, Suqi, Austern, Morgane
Format:	Preprint
Publié:	2026
Sujets:	Machine Learning Information Theory Social and Information Networks Statistics Theory
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Perfect Recovery for Random Geometric Graph Matching with Shallow Graph Neural Networks
par: Liu, Suqi, et autres
Publié: (2024)

Statistical Guarantees for Link Prediction using Graph Neural Networks
par: Chung, Alan, et autres
Publié: (2024)

Degree Heterogeneity in Higher-Order Networks: Inference in the Hypergraph $\boldsymbolβ$-Model
par: Nandy, Sagnik, et autres
Publié: (2023)

Spectral Clustering for Directed Graphs via Likelihood Estimation on Stochastic Block Models
par: Zhang, Ning, et autres
Publié: (2024)

Harnessing Multiple Correlated Networks for Exact Community Recovery
par: Rácz, Miklós Z., et autres
Publié: (2024)

Estimating Graph Dimension with Cross-validated Eigenvalues
par: Chen, Fan, et autres
Publié: (2021)

Two-way Node Popularity Model for Directed and Bipartite Networks
par: Jing, Bing-Yi, et autres
Publié: (2024)

Fundamental limits of community detection from multi-view data: multi-layer, dynamic and partially labeled block models
par: Yang, Xiaodong, et autres
Publié: (2024)

Exact Graph Matching in Correlated Gaussian-Attributed Erdős-Rényi Model
par: Yang, Joonhyuk, et autres
Publié: (2024)

Exact Matching in Correlated Networks with Node Attributes for Improved Community Recovery
par: Yang, Joonhyuk, et autres
Publié: (2025)

Network two-sample test for block models
par: Nguen, Chung Kyong, et autres
Publié: (2024)

Detecting Arbitrary Planted Subgraphs in Random Graphs
par: Elimelech, Dor, et autres
Publié: (2025)

Overfitting has a limitation: a model-independent generalization gap bound based on Rényi entropy
par: Suzuki, Atsushi, et autres
Publié: (2025)

Impossibility of latent inner product recovery via rate distortion
par: Mao, Cheng, et autres
Publié: (2024)

Information-Theoretic Thresholds for the Alignments of Partially Correlated Graphs
par: Huang, Dong, et autres
Publié: (2024)

Testing Correlation in Graphs by Counting Bounded Degree Motifs
par: Huang, Dong, et autres
Publié: (2025)

On Balancing Sparsity with Reliable Connectivity in Distributed Network Design with Random K-out Graphs
par: Sood, Mansi, et autres
Publié: (2025)

Spectral Graph Sparsification Preserves Representation Geometry in Graph Neural Networks
par: Krishnagopal, Sanjukta
Publié: (2026)

Efficient Graph Matching for Correlated Stochastic Block Models
par: Chai, Shuwen, et autres
Publié: (2024)

Multi-Community Spectral Clustering for Geometric Graphs
par: Allem, Luiz Emilio, et autres
Publié: (2025)

Sparse Max-Affine Regression
par: Kanj, Haitham, et autres
Publié: (2024)

Random geometric graphs with smooth kernels: sharp detection threshold and a spectral conjecture
par: Mao, Cheng, et autres
Publié: (2026)

Inferring Dynamic Networks from Marginals with Iterative Proportional Fitting
par: Chang, Serina, et autres
Publié: (2024)

Agnostic Sample Compression Schemes for Regression
par: Attias, Idan, et autres
Publié: (2018)

Max-Linear Regression by Convex Programming
par: Kim, Seonho, et autres
Publié: (2021)

Mixed Regression via Approximate Message Passing
par: Tan, Nelvin, et autres
Publié: (2023)

When Does Bottom-up Beat Top-down in Hierarchical Community Detection?
par: Dreveton, Maximilien, et autres
Publié: (2023)

Sparse graphs using exchangeable random measures
par: Caron, François, et autres
Publié: (2014)

Centrality Graph Shift Operators for Graph Neural Networks
par: Abbahaddou, Yassine, et autres
Publié: (2024)

Finding Super-spreaders in Network Cascades
par: Mossel, Elchanan, et autres
Publié: (2024)

Shape of Memory: a Geometric Analysis of Machine Unlearning in Second-Order Optimizers
par: Stewart, Kennon
Publié: (2026)

Detection of Correlated Random Vectors
par: Elimelech, Dor, et autres
Publié: (2024)

Information-Geometric Decomposition of Generalization Error in Unsupervised Learning
par: Kim, Gilhan
Publié: (2026)

Batches Stabilize the Minimum Norm Risk in High Dimensional Overparameterized Linear Regression
par: Ioushua, Shahar Stein, et autres
Publié: (2023)

Graph Attention Network for Optimal User Association in Wireless Networks
par: Mirzaei, Javad, et autres
Publié: (2025)

Causal Models for Growing Networks
par: Bravo-Hermsdorff, Gecia, et autres
Publié: (2025)

Random pairing MLE for estimation of item parameters in Rasch model
par: Yang, Yuepeng, et autres
Publié: (2024)

A Fast Binary Splitting Approach for Non-Adaptive Learning of Erdős--Rényi Graphs
par: Ta, Hoang, et autres
Publié: (2025)

Self-Attention Empowered Graph Convolutional Network for Structure Learning and Node Embedding
par: Jiang, Mengying, et autres
Publié: (2024)

Universality of High-Dimensional Logistic Regression and a Novel CGMT under Dependence with Applications to Data Augmentation
par: Mallory, Matthew Esmaili, et autres
Publié: (2025)