Deepest Minimum Criterion for Biased Affine Estimation. - Bruno Cernuschi-Frías; Fernando Gama; Daniel Casaglia (IEEE Trans. Signal Process., 2014)

Analysis and Comparison of Biased Affine Estimators. - Fernando Gama; Daniel Casaglia; Bruno Cernuschi-Frías (IEEE Trans. Signal Process., 2015)

Rethinking sketching as sampling: Linear transforms of graph signals. - Fernando Gama; Antonio G. Marques; Gonzalo Mateos; Alejandro Ribeiro (ACSSC, 2016)

Overlapping clustering of network data using cut metrics. - Fernando Gama; Santiago Segarra; Alejandro Ribeiro (ICASSP, 2016)

VCloud: adding interactiveness to word clouds for knowledge exploration in large unstructured texts. - Wallace P. Lira; Fernando Gama; Hivana Melo Barbosa Dall'Agnol; Ronnie Alves; Cleidson R. B. de Souza (SAC, 2016)

Distributed estimation of smooth graph power spectral density. - Fernando Gama; Alejandro Ribeiro (GlobalSIP, 2017)

Improving Our Understanding of the Behavior of Bees Through Anomaly Detection Techniques. - Fernando Gama; Helder M. Arruda; Hanna V. Carvalho; Paulo A. de Souza; Gustavo Pessin (ICANN (2), 2017)

Weak law of large numbers for stationary graph processes. - Fernando Gama; Alejandro Ribeiro (ICASSP, 2017)

Convolutional Neural Networks via Node-Varying Graph Filters. - Fernando Gama; Geert Leus; Antonio G. Marques; Alejandro Ribeiro (DSW, 2018)

CNN Architectures for Graph Data. - Fernando Gama; Antonio G. Marques; Geert Leus; Alejandro Ribeiro (GlobalSIP, 2018)

Predicting Power Outages Using Graph Neural Networks. - Damian Owerko; Fernando Gama; Alejandro Ribeiro (GlobalSIP, 2018)

Control of Graph Signals Over Random Time-Varying Graphs. - Fernando Gama; Elvin Isufi; Geert Leus; Alejandro Ribeiro (ICASSP, 2018)

MIMO Graph Filters for Convolutional Neural Networks. - Fernando Gama; Antonio G. Marques; Alejandro Ribeiro; Geert Leus (SPAWC, 2018)

Convolutional Neural Networks Architectures for Signals Supported on Graphs. - Fernando Gama; Antonio G. Marques; Geert Leus; Alejandro Ribeiro (CoRR, 2018)

Hierarchical Overlapping Clustering of Network Data Using Cut Metrics. - Fernando Gama; Santiago Segarra; Alejandro Ribeiro (IEEE Trans. Signal Inf. Process. over Networks, 2018)

Design Strategies for Sparse Control Of Random Time-Varying NETWORKS. - Mario Coutino; Elvin Isufi; Fernando Gama; Alejandro Ribeiro; Geert Leus (ACSSC, 2019)

Convolutional Graph Neural Networks. - Fernando Gama; Antonio G. Marques; Geert Leus; Alejandro Ribeiro (ACSSC, 2019)

Learning Decentralized Controllers for Robot Swarms with Graph Neural Networks. - Ekaterina I. Tolstaya; Fernando Gama; James Paulos; George J. Pappas; Vijay Kumar 001; Alejandro Ribeiro (CoRL, 2019)

Generalizing Graph Convolutional Neural Networks with Edge-Variant Recursions on Graphs. - Elvin Isufi; Fernando Gama; Alejandro Ribeiro (EUSIPCO, 2019)

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

Aggregation Graph Neural Networks. - Fernando Gama; Antonio G. Marques; Alejandro Ribeiro; Geert Leus (ICASSP, 2019)

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

Diffusion Scattering Transforms on Graphs. - Fernando Gama; Alejandro Ribeiro; Joan Bruna (ICLR (Poster), 2019)

Stability of Graph Scattering Transforms. - Fernando Gama; Alejandro Ribeiro; Joan Bruna (NeurIPS, 2019)

Controllability of Bandlimited Graph Processes Over Random Time Varying Graphs. - Fernando Gama; Elvin Isufi; Alejandro Ribeiro; Geert Leus (IEEE Trans. Signal Process., 2019)

Convolutional Neural Network Architectures for Signals Supported on Graphs. - Fernando Gama; Antonio G. Marques; Geert Leus; Alejandro Ribeiro (IEEE Trans. Signal Process., 2019)

Ergodicity in Stationary Graph Processes: A Weak Law of Large Numbers. - Fernando Gama; Alejandro Ribeiro (IEEE Trans. Signal Process., 2019)

Graph Neural Networks for Decentralized Path Planning. - Qingbiao Li; Fernando Gama; Alejandro Ribeiro; Amanda Prorok (AAMAS, 2020)

Stability of Graph Neural Networks to Relative Perturbations. - Fernando Gama; Alejandro Ribeiro; Joan Bruna (ICASSP, 2020)

Optimal Power Flow Using Graph Neural Networks. - Damian Owerko; Fernando Gama; Alejandro Ribeiro (ICASSP, 2020)

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

Graph Neural Networks for Decentralized Multi-Robot Path Planning. - Qingbiao Li; Fernando Gama; Alejandro Ribeiro; Amanda Prorok (IROS, 2020)

VGAI: A Vision-Based Decentralized Controller Learning Framework for Robot Swarms. - Ting-Kuei Hu; Fernando Gama; Zhangyang Wang; Alejandro Ribeiro; Brian M. Sadler (CoRR, 2020)

Graphs, Convolutions, and Neural Networks. - Fernando Gama; Elvin Isufi; Geert Leus; Alejandro Ribeiro (CoRR, 2020)

Decentralized Control with Graph Neural Networks. - Fernando Gama; Qingbiao Li; Ekaterina I. Tolstaya; Amanda Prorok; Alejandro Ribeiro (CoRR, 2020)

Rethinking sketching as sampling: A graph signal processing approach. - Fernando Gama; Antonio G. Marques; Gonzalo Mateos; Alejandro Ribeiro (Signal Process., 2020)

Graphs, Convolutions, and Neural Networks: From Graph Filters to Graph Neural Networks. - Fernando Gama; Elvin Isufi; Geert Leus; Alejandro Ribeiro (IEEE Signal Process. Mag., 2020)

Stability Properties of Graph Neural Networks. - Fernando Gama; Joan Bruna; Alejandro Ribeiro (IEEE Trans. Signal Process., 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)

A Robust Alternative for Graph Convolutional Neural Networks via Graph Neighborhood Filters. - Victor M. Tenorio; Samuel Rey; Fernando Gama; Santiago Segarra; Antonio G. Marques (ACSCC, 2021)

Stability of Spherical Convolutional Neural Networks to Rotation Diffeomorphisms. - Zhan Gao; Fernando Gama; Alejandro Ribeiro (EUSIPCO, 2021)

Graph Neural Networks for Decentralized Controllers. - Fernando Gama; Ekaterina I. Tolstaya; Alejandro Ribeiro (ICASSP, 2021)

Wide and Deep Graph Neural Networks with Distributed Online Learning. - Zhan Gao; Alejandro Ribeiro; Fernando Gama (ICASSP, 2021)

VGAI: End-to-End Learning of Vision-Based Decentralized Controllers for Robot Swarms. - Ting-Kuei Hu; Fernando Gama; Tianlong Chen 001; Zhangyang Wang; Alejandro Ribeiro; Brian M. Sadler (ICASSP, 2021)

Discriminability of Single-Layer Graph Neural Networks. - Samuel Pfrommer; Alejandro Ribeiro; Fernando Gama (ICASSP, 2021)

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

Graph Neural Networks for Distributed Linear-Quadratic Control. - Fernando Gama; Somayeh Sojoudi (L4DC, 2021)

Node-Variant Graph Filters in Graph Neural Networks. - Fernando Gama; Brendon G. Anderson; Somayeh Sojoudi (CoRR, 2021)

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

Distributed Optimal Control of Graph Symmetric Systems via Graph Filters. - Fengjun Yang; Fernando Gama; Somayeh Sojoudi; Nikolai Matni (CDC, 2022)

Stability Analysis of Unfolded WMMSE for Power Allocation. - Arindam Chowdhury; Fernando Gama; Santiago Segarra (ICASSP, 2022)

Unrolling Particles: Unsupervised Learning of Sampling Distributions. - Fernando Gama; Nicolas Zilberstein; Richard G. Baraniuk; Santiago Segarra (ICASSP, 2022)

EdgeNets: Edge Varying Graph Neural Networks. - Elvin Isufi; Fernando Gama; Alejandro Ribeiro (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Distributed linear-quadratic control with graph neural networks. - Fernando Gama; Somayeh Sojoudi (Signal Process., 2022)

Spherical convolutional neural networks: Stability to perturbations in SO(3). - Zhan Gao; Fernando Gama; Alejandro Ribeiro (Signal Process., 2022)

Scalable Perception-Action-Communication Loops With Convolutional and Graph Neural Networks. - Ting-Kuei Hu; Fernando Gama; Tianlong Chen 001; Wenqing Zheng; Zhangyang Wang; Alejandro Ribeiro; Brian M. Sadler (IEEE Trans. Signal Inf. Process. over Networks, 2022)

Synthesizing Decentralized Controllers With Graph Neural Networks and Imitation Learning. - Fernando Gama; Qingbiao Li; Ekaterina I. Tolstaya; Amanda Prorok; Alejandro Ribeiro (IEEE Trans. Signal Process., 2022)

Wide and Deep Graph Neural Network With Distributed Online Learning. - Zhan Gao; Fernando Gama; Alejandro Ribeiro (IEEE Trans. Signal Process., 2022)

On Local Distributions in Graph Signal Processing. - T. Mitchell Roddenberry; Fernando Gama; Richard G. Baraniuk; Santiago Segarra (IEEE Trans. Signal Process., 2022)

Distributed Power System State Estimation Using Graph Convolutional Neural Networks. - Sangwoo Park 004; Fernando Gama; Javad Lavaei; Somayeh Sojoudi (HICSS, 2023)

Stability of Aggregation Graph Neural Networks. - Alejandro Parada-Mayorga; Zhiyang Wang; Fernando Gama; Alejandro Ribeiro (IEEE Trans. Signal Inf. Process. over Networks, 2023)

Unsupervised Learning of Sampling Distributions for Particle Filters. - Fernando Gama; Nicolas Zilberstein; Martin Sevilla; Richard G. Baraniuk; Santiago Segarra (IEEE Trans. Signal Process., 2023)

Unsupervised Optimal Power Flow Using Graph Neural Networks. - Damian Owerko; Fernando Gama; Alejandro Ribeiro (ICASSP, 2024)

Distributed UAV Beamforming Using Graph Recurrent Neural Networks. - Wenqing Zheng; Brian M. Sadler; Fernando Gama; Tianlong Chen 001 (SAM, 2024)

Graph Filters for Signal Processing and Machine Learning on Graphs. - Elvin Isufi; Fernando Gama; David I Shuman; Santiago Segarra (IEEE Trans. Signal Process., 2024)