Cover Image

Beyond the Laplacian: Doubly Stochastic Matrices for Graph Neural Networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Hu, Zhaobo, Gauthier, Vincent, Naima, Mehdi
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Modern Structure-Aware Simplicial Spatiotemporal Neural Network
by: Hu, Zhaobo, et al.
Published: (2026)

Reversible Residual Normalization Alleviates Spatio-Temporal Distribution Shift
by: Hu, Zhaobo, et al.
Published: (2026)

Row-Stochastic Matrices Can Provably Outperform Doubly Stochastic Matrices in Decentralized Learning
by: Liu, Bing, et al.
Published: (2025)

Beyond the Laplacian: Interpolated Spectral Augmentation for Graph Neural Networks
by: Cui, Ziyao, et al.
Published: (2025)

Doubly Stochastic Matrices and Modified Laplacian Matrices of Graphs
by: Andrade, Enide, et al.
Published: (2025)

Enhancing Robustness of Graph Neural Networks through p-Laplacian
by: Sirohi, Anuj Kumar, et al.
Published: (2025)

Enhancing Robustness of Graph Neural Networks through p-Laplacian
by: Sirohi, Anuj Kumar, et al.
Published: (2024)

Learning Useful Representations of Recurrent Neural Network Weight Matrices
by: Herrmann, Vincent, et al.
Published: (2024)

A Graph Laplacian Eigenvector-based Pre-training Method for Graph Neural Networks
by: Dai, Howard, et al.
Published: (2025)

Pruning and Quantization Impact on Graph Neural Networks
by: Khedri, Khatoon, et al.
Published: (2025)

The Homogeneity Trap: Spectral Collapse in Doubly-Stochastic Deep Networks
by: Liu, Yizhi
Published: (2026)

Large-Scale Spectral Graph Neural Networks via Laplacian Sparsification: Technical Report
by: Ding, Haipeng, et al.
Published: (2025)

Partially Observable Gaussian Process Network and Doubly Stochastic Variational Inference
by: Kiroriwal, Saksham, et al.
Published: (2025)

Demystifying SGD with Doubly Stochastic Gradients
by: Kim, Kyurae, et al.
Published: (2024)

Network Distance Based on Laplacian Flows on Graphs
by: Bao, Dianbin, et al.
Published: (2018)

Doubly Robust Conditional Independence Testing with Generative Neural Networks
by: Zhang, Yi, et al.
Published: (2024)

A Laplacian-based Quantum Graph Neural Network for Semi-Supervised Learning
by: Gholipour, Hamed, et al.
Published: (2024)

Predicting the Performance of Graph Convolutional Networks with Spectral Properties of the Graph Laplacian
by: Manir, Shalima Binta, et al.
Published: (2025)

ESPFormer: Doubly-Stochastic Attention with Expected Sliced Transport Plans
by: Shahbazi, Ashkan, et al.
Published: (2025)

Graph Pseudotime Analysis and Neural Stochastic Differential Equations for Analyzing Retinal Degeneration Dynamics and Beyond
by: Shi, Dai, et al.
Published: (2025)

Doubly Stochastic Mean-Shift Clustering
by: Trigano, Tom, et al.
Published: (2026)

Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations
by: Bergna, Richard, et al.
Published: (2024)

ASAP: Amortized Doubly-Stochastic Attention via Sliced Dual Projection
by: Tran, Huy, et al.
Published: (2026)

ASEHybrid: When Geometry Matters Beyond Homophily in Graph Neural Networks
by: Manir, Shalima Binta, et al.
Published: (2026)

Network Tomography with Path-Centric Graph Neural Network
by: Hu, Yuntong, et al.
Published: (2025)

Graph ODEs and Beyond: A Comprehensive Survey on Integrating Differential Equations with Graph Neural Networks
by: Liu, Zewen, et al.
Published: (2025)

Beyond Empirical Windowing: An Attention-Based Approach for Trust Prediction in Autonomous Vehicles
by: Niu, Minxue, et al.
Published: (2023)

Performative Prediction with Neural Networks
by: Mofakhami, Mehrnaz, et al.
Published: (2023)

LOTFormer: Doubly-Stochastic Linear Attention via Low-Rank Optimal Transport
by: Shahbazi, Ashkan, et al.
Published: (2025)

Proving Linear Mode Connectivity of Neural Networks via Optimal Transport
by: Ferbach, Damien, et al.
Published: (2023)

Doubly Stochastic Adaptive Neighbors Clustering via the Marcus Mapping
by: Yuan, Jinghui, et al.
Published: (2024)

Beyond Neural Networks: Symbolic Reasoning over Wavelet Logic Graph Signals
by: Kiruluta, Andrew, et al.
Published: (2025)

Beyond Over-smoothing: Uncovering the Trainability Challenges in Deep Graph Neural Networks
by: Peng, Jie, et al.
Published: (2024)

ES-GNN: Generalizing Graph Neural Networks Beyond Homophily with Edge Splitting
by: Guo, Jingwei, et al.
Published: (2022)

Probing Graph Neural Network Activation Patterns Through Graph Topology
by: Tori, Floriano, et al.
Published: (2026)

Asymptotic Theory of Eigenvectors for Latent Embeddings with Generalized Laplacian Matrices
by: Fan, Jianqing, et al.
Published: (2025)

Doubly Robust Proxy Causal Learning with Neural Mean Embeddings
by: Bozkurt, Bariscan, et al.
Published: (2026)

Resolving Node Identifiability in Graph Neural Processes via Laplacian Spectral Encodings
by: Yan, Zimo, et al.
Published: (2025)

Beyond Edge Deletion: A Comprehensive Approach to Counterfactual Explanation in Graph Neural Networks
by: De Sanctis, Matteo, et al.
Published: (2026)

Quantum Doubly Stochastic Transformers
by: Born, Jannis, et al.
Published: (2025)