{"total":53,"rows":[{"id":"2302.12432","title":"Graph Neural Networks with Learnable and Optimal Polynomial Bases","created":"2023-02-24","cited_by_count":36,"area":null},{"id":"2307.00494","title":"Improving Protein Optimization with Smoothed Fitness Landscapes","created":"2023-07-02","cited_by_count":21,"area":null},{"id":"2511.20030","title":"Cross-Contrastive Clustering for Multimodal Attributed Graphs with Dual Graph Filtering","created":"2025-11-25","cited_by_count":14,"area":null},{"id":"2409.10068","title":"Spatiotemporal Covariance Neural Networks","created":"2024-09-16","cited_by_count":9,"area":null},{"id":"2303.11459","title":"Fairness-Aware Graph Filter Design","created":"2023-03-20","cited_by_count":8,"area":null},{"id":"2409.08676","title":"Redesigning graph filter-based GNNs to relax the homophily assumption","created":"2024-09-13","cited_by_count":8,"area":null},{"id":"2510.05036","title":"Graph-Aware Diffusion for Signal Generation","created":"2025-10-06","cited_by_count":8,"area":null},{"id":"2410.01669","title":"Sparse Covariance Neural Networks","created":"2024-10-02","cited_by_count":7,"area":null},{"id":"2409.08558","title":"Fair CoVariance Neural Networks","created":"2024-09-13","cited_by_count":6,"area":null},{"id":"2309.09068","title":"Recovering Missing Node Features with Local Structure-based Embeddings","created":"2023-09-16","cited_by_count":5,"area":null},{"id":"2503.11470","title":"Topological Dictionary Learning","created":"2025-03-14","cited_by_count":4,"area":null},{"id":"2505.11139","title":"Covariance Density Neural Networks","created":"2025-05-16","cited_by_count":4,"area":null},{"id":"2510.12763","title":"Disentangling Neurodegeneration with Brain Age Gap Prediction Models: A Graph Signal Processing Perspective","created":"2025-10-14","cited_by_count":3,"area":null},{"id":"2511.15327","title":"KrawtchoukNet: A Unified GNN Solution for Heterophily and Over-smoothing with Adaptive Bounded Polynomials","created":"2025-11-19","cited_by_count":3,"area":null},{"id":"2310.14432","title":"Fairness-aware Optimal Graph Filter Design","created":"2023-10-22","cited_by_count":2,"area":null},{"id":"2312.02372","title":"On the Trade-Off between Stability and Representational Capacity in Graph Neural Networks","created":"2023-12-04","cited_by_count":2,"area":null},{"id":"2409.08660","title":"Online Learning Of Expanding Graphs","created":"2024-09-13","cited_by_count":2,"area":null},{"id":"2503.04406","title":"Training-free Adjustable Polynomial Graph Filtering for Ultra-fast Multimodal Recommendation","created":"2025-03-06","cited_by_count":2,"area":null},{"id":"2505.23160","title":"Topological Adaptive Least Mean Squares Algorithms over Simplicial Complexes","created":"2025-05-29","cited_by_count":2,"area":null},{"id":"2506.22004","title":"GKNet: Graph Kalman Filtering and Model Inference via Model-based Deep Learning","created":"2025-06-27","cited_by_count":2,"area":null},{"id":"2511.15328","title":"LaguerreNet: Advancing a Unified Solution for Heterophily and Over-smoothing with Adaptive Continuous Polynomials","created":"2025-11-19","cited_by_count":2,"area":null},{"id":"2607.07510","title":"Stability of Flow Models for Graph Signals","created":"2026-07-08","cited_by_count":2,"area":null},{"id":"2609.10490","title":"Learning with Covariance Matrices: Principal Component Analysis Meets Learning with Graphs","created":"2026-09-09","cited_by_count":2,"area":null},{"id":"2311.02838","title":"Barron Space for Graph Convolution Neural Networks","created":"2023-11-06","cited_by_count":1,"area":null},{"id":"2409.07204","title":"Online Graph Filtering Over Expanding Graphs","created":"2024-09-11","cited_by_count":1,"area":null},{"id":"2410.17410","title":"Learning Graph Filters for Structure-Function Coupling based Hub Node Identification","created":"2024-10-22","cited_by_count":1,"area":null},{"id":"2411.01070","title":"Explainable Spatio-Temporal GCNNs for Irregular Multivariate Time Series: Architecture and Application to ICU Patient Data","created":"2024-11-01","cited_by_count":1,"area":null},{"id":"2411.15527","title":"Haar-Laplacian for directed graphs","created":"2024-11-23","cited_by_count":1,"area":null},{"id":"2502.20885","title":"A Fused Gromov-Wasserstein Approach to Subgraph Contrastive Learning","created":"2025-02-28","cited_by_count":1,"area":null},{"id":"2506.10628","title":"Leveraging Low-rank Factorizations of Conditional Correlation Matrices in Graph Learning","created":"2025-06-12","cited_by_count":1,"area":null},{"id":"2506.12218","title":"Directed Acyclic Graph Convolutional Networks","created":"2025-06-13","cited_by_count":1,"area":null},{"id":"2509.25802","title":"Graph Distribution-valued Signals: A Wasserstein Space Perspective","created":"2025-09-30","cited_by_count":1,"area":null},{"id":"2602.06557","title":"Which Graph Shift Operator? A Spectral Answer to an Empirical Question","created":"2026-02-06","cited_by_count":1,"area":null},{"id":"2404.12724","title":"Graph Convolutional Network For Semi-supervised Node Classification With Subgraph Sketching","created":"2024-04-19","cited_by_count":0,"area":null},{"id":"2412.17734","title":"LASE: Learned Adjacency Spectral Embeddings","created":"2024-12-23","cited_by_count":0,"area":null},{"id":"2502.00585","title":"Converting Transformers into DGNNs Form","created":"2025-02-01","cited_by_count":0,"area":null},{"id":"2504.04576","title":"Cramer-Rao Bounds for Laplacian Matrix Estimation","created":"2025-04-06","cited_by_count":0,"area":null},{"id":"2506.01213","title":"On the Stability of Graph Convolutional Neural Networks: A Probabilistic Perspective","created":"2025-06-01","cited_by_count":0,"area":null},{"id":"2506.01404","title":"Quantitative Error Feedback for Quantization Noise Reduction of Filtering over Graphs","created":"2025-06-02","cited_by_count":0,"area":null},{"id":"2506.16602","title":"SlepNet: Spectral Subgraph Representation Learning for Neural Dynamics","created":"2025-06-19","cited_by_count":0,"area":null},{"id":"2507.09717","title":"Signed Graph Learning: Algorithms and Theory","created":"2025-07-13","cited_by_count":0,"area":null},{"id":"2507.21705","title":"Unrolling Dynamic Programming via Graph Filters","created":"2025-07-29","cited_by_count":0,"area":null},{"id":"2508.16633","title":"A Novel Unified Extended Matrix for Graph Signal Processing: Theory and Application","created":"2025-08-16","cited_by_count":0,"area":null},{"id":"2509.13178","title":"CoVariance Filters and Neural Networks over Hilbert Spaces","created":"2025-09-16","cited_by_count":0,"area":null},{"id":"2509.20311","title":"Graph Variate Neural Networks","created":"2025-09-24","cited_by_count":0,"area":null},{"id":"2511.16111","title":"Rotation-Parameterized Graph Fractional Fourier Transform: Definition, Properties, and Optimal Filtering","created":"2025-11-20","cited_by_count":0,"area":null},{"id":"2602.10031","title":"Graph Learning Should Move Beyond Restrictive Views of Spectral and Message-Passing GNNs","created":"2026-02-10","cited_by_count":0,"area":null},{"id":"2602.15920","title":"Including Node Textual Metadata in Laplacian-constrained Gaussian Graphical Models","created":"2026-02-17","cited_by_count":0,"area":null},{"id":"2603.19439","title":"Subspace Projection Methods for Fast Spectral Embeddings of Evolving Graphs","created":"2026-03-19","cited_by_count":0,"area":null},{"id":"2603.19501","title":"Stochastic Sequential Decision Making over Expanding Networks with Graph Filtering","created":"2026-03-19","cited_by_count":0,"area":null},{"id":"2603.20338","title":"Low-pass Personalized Subgraph Federated Recommendation","created":"2026-03-20","cited_by_count":0,"area":null},{"id":"2605.04957","title":"Delving into Non-Exchangeability for Conformal Prediction in Graph-Structured Multivariate Time Series","created":"2026-05-06","cited_by_count":0,"area":null},{"id":"2609.18759","title":"Stable Filters for Generative Modeling of Graph Signals","created":"2026-09-16","cited_by_count":0,"area":null}],"next_cursor":null}