Publications

Publications by categories in reversed chronological order. Generated by jekyll-scholar.

2025

  1. Local Distance-Preserving Node Embeddings and Their Performance on Random Graphs
    My Le, Luana Ruiz, and Souvik Dhara
    arXiv preprint arXiv:2504.08216, 2025
  2. Improved Image Classification with Manifold Neural Networks
    Caio F. Deberaldini Netto, Zhiyang Wang, and Luana Ruiz
    In 50th ICASSP, 2025
  3. A Generative Model for Controllable Feature Homophily in Graphs
    H. Wang, R. Ma, G. Mateos, and L. Ruiz
    arXiv preprint arXiv:2509.23230, 2025
    Submitted to ICASSP 2026
  4. Graph Semi-Supervised Learning for Point Classification on Data Manifolds
    Caio F. Deberaldini Netto, Zhiyang Wang, and Luana Ruiz
    arXiv preprint arXiv:2506.12197, 2025
    Submitted to IEEE TSP
  5. Subsampling Graphs with GNN Performance Guarantees
    M. Jain, S. Jegelka, I. Karmarkar, L.a Ruiz, and E. Vitercik
    arXiv preprint arXiv:2502.16703, 2025
  6. A Local Graph Limits Perspective on Sampling-Based Graph Neural Networks
    Yeganeh Alimohammadi, Luana Ruiz, and Amin Saberi
    In 2025 IEEE International Symposium on Information Theory (ISIT), 2025
  7. Dirichlet Meets Horvitz and Thompson: Estimating Homophily in Large Graphs via Sampling
    H. Ajorlou, L. Ruiz, and G. Mateos
    In 59th Asilomar Conf. on Sig. and Syst., 2025
    To appear
  8. Graph Sampling for Scalable and Expressive Graph Neural Networks on Homophilic Graphs
    Haolin Li, Haoyu Wang, and Luana Ruiz
    In 33rd European Signal Processing Conference (EUSIPCO), 2025

2024

  1. Stability to Deformations of Manifold Filters and Manifold Neural Networks
    Z. Wang, L. Ruiz, and A. Ribeiro
    IEEE Trans. Signal Process., 2024
  2. Geometric Graph Filters and Neural Networks: Limit Properties and Discriminability Trade-offs
    Z. Wang, L. Ruiz, and A. Ribeiro
    IEEE Trans. Signal Process., 2024
  3. A Poincaré Inequality and Consistency Results for Signal Sampling on Large Graphs (Spotlight)
    T. Le, L. Ruiz, and S. Jegelka
    In 12th ICLR, 7–11 may 2024
  4. A Spectral Analysis of Graph Neural Networks on Dense and Sparse Graphs
    L. Ruiz, N. Huang, and S. Villar
    In 49th ICASSP, 14-19 apr. 2024

2023

  1. Learning by Transference: Training Graph Neural Networks on Growing Graphs
    J. Cervino, L. Ruiz, and A. Ribeiro
    IEEE Trans. Signal Process., 14-19 apr. 2023
  2. Transferability Properties of Graph Neural Networks
    L. Ruiz, L. F. O. Chamon, and A. Ribeiro
    IEEE Trans. Signal Process., 14-19 apr. 2023
  3. Graph Neural Tangent Kernel: Convergence on Large Graphs
    S. Krishnagopal, and L. Ruiz
    In 40th ICML, 23-29 jul. 2023
  4. Convolutional Filtering on Sampled Manifolds
    Z. Wang, L Ruiz, and A. Ribeiro
    In 48th ICASSP, 4-10 jun. 2023
  5. Training Graph Neural Networks on Growing Stochastic Graphs
    J/ Cerviño, L. Ruiz, and A. Ribeiro
    In 48th ICASSP, 4-10 jun. 2023

2022

  1. Stability of Neural Networks on Manifolds to Relative Perturbations
    Z. Wang, L. Ruiz, and A. Ribeiro
    In 47th ICASSP, 22-27 may 2022
  2. Stable and Transferable Wireless Resource Allocation Policies via Manifold Neural Networks
    Z. Wang, L. Ruiz, M. Eisen, and A. Ribeiro
    In 47th ICASSP, 22-27 may 2022
  3. Training Stable Graph Neural Networks through Constrained Learning
    J/ Cerviño, L. Ruiz, and A. Ribeiro
    In 47th ICASSP, 22-27 may 2022
  4. Convolutional neural networks on manifolds: From graphs and back
    Z. Wang, L. Ruiz, and A. Ribeiro
    In 56th Asilomar Conf. on Sig. and Syst., 22-27 may 2022

2021

  1. Graph Neural Networks: Architectures, Stability and Transferability
    L. Ruiz, F. Gama, and A. Ribeiro
    Proc. IEEE, 22-27 may 2021
  2. Graphon Signal Processing
    L. Ruiz, L. F. O. Chamon, and A. Ribeiro
    Trans. Signal Process., 22-27 may 2021
  3. Graphon Filters: Signal Processing in Very Large Graphs
    L. Ruiz, L. F. O. Chamon, and A. Ribeiro
    In 28th EUSIPCO, 18-22 jan. 2021
  4. Graphon Pooling in Graph Neural Networks
    A. Parada-Mayorga, L. Ruiz, and A. Ribeiro
    In 28th EUSIPCO, 18-22 jan. 2021
  5. Stability of Neural Networks on Riemannian Manifolds (Best Paper Award)
    Z. Wang, L. Ruiz, and A. Ribeiro
    In 29th EUSIPCO, 23-27 aug. 2021
  6. Graphon and Graph Neural Network Stability
    L. Ruiz, Z. Wang, and A. Ribeiro
    In 46th ICASSP, 6-11 jun. 2021
  7. Nonlinear State-Space Generalizations of Graph Convolutional Neural Networks
    L. Ruiz, F. Gama, A. Ribeiro, and E. Isufi
    In 46th ICASSP, 6-11 jun. 2021
  8. Iterative Decoding for Compositional Generalization in Transformers
    L. Ruiz, J. Ainslie, and S. Ontañón
    arXiv:2110.04169 [cs.LG], 6-11 jun. 2021
  9. Transferable Graph Neural Networks on Large-Scale Stochastic Graphs
    L. Ruiz, L. F. O. Chamon, and A. Ribeiro
    In 55th Asilomar Conf. on Sig. and Syst., 6-11 jun. 2021

2020

  1. Invariance-Preserving Localized Activation Functions for Graph Neural Networks
    L. Ruiz, F. Gama, A. G. Marques, and A. Ribeiro
    Trans. Signal Process., 6-11 jun. 2020
  2. Gated Graph Recurrent Neural Networks
    L. Ruiz, F. Gama, and A. Ribeiro
    Trans. Signal Process., 6-11 jun. 2020
  3. Spatial Gating Strategies for Graph Recurrent Neural Networks
    L. Ruiz, F. Gama, and A. Ribeiro
    In 45th ICASSP, 4-8 may 2020
  4. The Graphon Fourier Transform
    L. Ruiz, L. F. O. Chamon, and A. Ribeiro
    In 45th ICASSP, 4-8 may 2020
  5. Graphon Neural Networks and the Transferability of Graph Neural Networks
    L. Ruiz, L. F. O. Chamon, and A. Ribeiro
    In 34th NeurIPS, 6-12 dec. 2020
  6. Graph-Adaptive Activation Functions for Graph Neural Networks
    B. Iancu, L. Ruiz, A. Ribeiro, and E. Isufi
    In 30th Int. Workshop Mach. Learn. Signal Process., 21-24 sep. 2020

2019

  1. Median Activation Functions for Graph Neural Networks
    L. Ruiz, F. Gama, A. G. Marques, and A. Ribeiro
    In 44th ICASSP, 13-17 may 2019
  2. Gated Graph Convolutional Recurrent Neural Networks (Best Paper Award)
    L. Ruiz, F. Gama, and A. Ribeiro
    In 27th EUSIPCO, 2-6 sep. 2019