Gated Graph Convolutional Recurrent Neural Networks. - Luana Ruiz; Fernando Gama; Alejandro Ribeiro (EUSIPCO, 2019)

Median Activation Functions for Graph Neural Networks. - Luana Ruiz; Fernando Gama; Antonio G. Marques; Alejandro Ribeiro (ICASSP, 2019)

Graphon Pooling in Graph Neural Networks. - Alejandro Parada-Mayorga; Luana Ruiz; Alejandro Ribeiro (EUSIPCO, 2020)

Graphon Filters: Signal Processing in Very Large Graphs. - Luana Ruiz; Luiz F. O. Chamon; Alejandro Ribeiro (EUSIPCO, 2020)

The Graphon Fourier Transform. - Luana Ruiz; Luiz F. O. Chamon; Alejandro Ribeiro (ICASSP, 2020)

Spatial Gating Strategies for Graph Recurrent Neural Networks. - Luana Ruiz; Fernando Gama; Alejandro Ribeiro (ICASSP, 2020)

Graph-Adaptive Activation Functions for Graph Neural Networks. - Bianca Iancu; Luana Ruiz; Alejandro Ribeiro; Elvin Isufi (MLSP, 2020)

Graphon Neural Networks and the Transferability of Graph Neural Networks. - Luana Ruiz; Luiz F. O. Chamon; Alejandro Ribeiro (NeurIPS, 2020)

Graph and graphon neural network stability. - Luana Ruiz; Zhiyang Wang; Alejandro Ribeiro (CoRR, 2020)

Invariance-Preserving Localized Activation Functions for Graph Neural Networks. - Luana Ruiz; Fernando Gama; Antonio Garcia Marques; Alejandro Ribeiro (IEEE Trans. Signal Process., 2020)

Gated Graph Recurrent Neural Networks. - Luana Ruiz; Fernando Gama; Alejandro Ribeiro (IEEE Trans. Signal Process., 2020)

Transferable Graph Neural Networks on Large-Scale Stochastic Graphs. - Luana Ruiz; Luiz F. O. Chamon; Alejandro Ribeiro (ACSCC, 2021)

Stability of Neural Networks on Riemannian Manifolds. - Zhiyang Wang; Luana Ruiz; Alejandro Ribeiro (EUSIPCO, 2021)

Nonlinear State-Space Generalizations of Graph Convolutional Neural Networks. - Luana Ruiz; Fernando Gama; Alejandro Ribeiro; Elvin Isufi (ICASSP, 2021)

Graphon and Graph Neural Network Stability. - Luana Ruiz; Zhiyang Wang; Alejandro Ribeiro (ICASSP, 2021)

Increase and Conquer: Training Graph Neural Networks on Growing Graphs. - Juan Cerviño; Luana Ruiz; Alejandro Ribeiro (CoRR, 2021)

Stability of Manifold Neural Networks to Deformations. - Zhiyang Wang; Luana Ruiz; Alejandro Ribeiro (CoRR, 2021)

Iterative Decoding for Compositional Generalization in Transformers. - Luana Ruiz; Joshua Ainslie; Santiago Ontañón (CoRR, 2021)

Graph Neural Networks: Architectures, Stability, and Transferability. - Luana Ruiz; Fernando Gama; Alejandro Ribeiro (Proc. IEEE, 2021)

Graphon Signal Processing. - Luana Ruiz; Luiz F. O. Chamon; Alejandro Ribeiro (IEEE Trans. Signal Process., 2021)

Convolutional Neural Networks on Manifolds: From Graphs and Back. - Zhiyang Wang; Luana Ruiz; Alejandro Ribeiro (IEEECONF, 2022)

Training Stable Graph Neural Networks Through Constrained Learning. - Juan Cerviño; Luana Ruiz; Alejandro Ribeiro (ICASSP, 2022)

Stable and Transferable Wireless Resource Allocation Policies Via Manifold Neural Networks. - Zhiyang Wang; Luana Ruiz; Mark Eisen; Alejandro Ribeiro (ICASSP, 2022)

Stability of Neural Networks on Manifolds to Relative Perturbations. - Zhiyang Wang; Luana Ruiz; Alejandro Ribeiro (ICASSP, 2022)

Graph Neural Networks for Community Detection on Sparse Graphs. - Luana Ruiz; Ningyuan Huang; Soledad Villar (CoRR, 2022)

Convergence of Graph Neural Networks on Relatively Sparse Graphs. - Zhiyang Wang; Luana Ruiz; Alejandro Ribeiro (ACSSC, 2023)

Training Graph Neural Networks on Growing Stochastic Graphs. - Juan Cerviño; Luana Ruiz; Alejandro Ribeiro (ICASSP, 2023)

Convolutional Filtering on Sampled Manifolds. - Zhiyang Wang; Luana Ruiz; Alejandro Ribeiro (ICASSP, 2023)

Graph Neural Tangent Kernel: Convergence on Large Graphs. - Sanjukta Krishnagopal; Luana Ruiz (ICML, 2023)

A Local Graph Limits Perspective on Sampling-Based GNNs. - Yeganeh Alimohammadi; Luana Ruiz; Amin Saberi (CoRR, 2023)

Learning by Transference: Training Graph Neural Networks on Growing Graphs. - Juan Cerviño; Luana Ruiz; Alejandro Ribeiro (IEEE Trans. Signal Process., 2023)

Transferability Properties of Graph Neural Networks. - Luana Ruiz; Luiz F. O. Chamon; Alejandro Ribeiro (IEEE Trans. Signal Process., 2023)

A Spectral Analysis of Graph Neural Networks on Dense and Sparse Graphs. - Luana Ruiz; Ningyuan Teresa Huang; Soledad Villar (ICASSP, 2024)

A Poincaré Inequality and Consistency Results for Signal Sampling on Large Graphs. - Thien Le; Luana Ruiz; Stefanie Jegelka (ICLR, 2024)

Graph Sampling for Scalable and Expressive Graph Neural Networks on Homophilic Graphs. - Haolin Li; Luana Ruiz (CoRR, 2024)

Stability to Deformations of Manifold Filters and Manifold Neural Networks. - Zhiyang Wang; Luana Ruiz; Alejandro Ribeiro (IEEE Trans. Signal Process., 2024)

Geometric Graph Filters and Neural Networks: Limit Properties and Discriminability Trade-Offs. - Zhiyang Wang; Luana Ruiz; Alejandro Ribeiro (IEEE Trans. Signal Process., 2024)

Improved Image Classification with Manifold Neural Networks. - Caio F. Deberaldini Netto; Zhiyang Wang; Luana Ruiz (ICASSP, 2025)

Subsampling Graphs with GNN Performance Guarantees. - Mika Sarkin Jain; Stefanie Jegelka; Ishani Karmarkar; Luana Ruiz; Ellen Vitercik (CoRR, 2025)

Local Distance-Preserving Node Embeddings and Their Performance on Random Graphs. - My Le; Luana Ruiz; Souvik Dhara (CoRR, 2025)

Graph Semi-Supervised Learning for Point Classification on Data Manifolds. - Caio F. Deberaldini Netto; Zhiyang Wang; Luana Ruiz (CoRR, 2025)