Fernando Gama

Publication Activity (10 Years)

Years Active: 2014-2023
Publications (10 Years): 98

Top Topics

Decentralized Control

Top Venues

IEEE Trans. Signal Process.

Signal Process.

Publications

Sangwoo Park, Fernando Gama, Javad Lavaei, Somayeh Sojoudi
Distributed Power System State Estimation Using Graph Convolutional Neural Networks. HICSS (2023)
Alejandro Parada-Mayorga, Zhiyang Wang, Fernando Gama, Alejandro Ribeiro
Stability of Aggregation Graph Neural Networks. IEEE Trans. Signal Inf. Process. over Networks 9 (2023)
Fernando Gama, Nicolas Zilberstein, Martin Sevilla, Richard G. Baraniuk, Santiago Segarra
Unsupervised Learning of Sampling Distributions for Particle Filters. IEEE Trans. Signal Process. 71 (2023)
Fengjun Yang, Fernando Gama, Somayeh Sojoudi, Nikolai Matni
Distributed Optimal Control of Graph Symmetric Systems via Graph Filters. CDC (2022)
Zhan Gao, Fernando Gama, Alejandro Ribeiro
Spherical convolutional neural networks: Stability to perturbations in SO(3). Signal Process. 196 (2022)
Elvin Isufi, Fernando Gama, Alejandro Ribeiro
EdgeNets: Edge Varying Graph Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. 44 (11) (2022)
Zhan Gao, Fernando Gama, Alejandro Ribeiro
Wide and Deep Graph Neural Network With Distributed Online Learning. IEEE Trans. Signal Process. 70 (2022)
Fernando Gama, Qingbiao Li, Ekaterina I. Tolstaya, Amanda Prorok, Alejandro Ribeiro
Synthesizing Decentralized Controllers With Graph Neural Networks and Imitation Learning. IEEE Trans. Signal Process. 70 (2022)
T. Mitchell Roddenberry, Fernando Gama, Richard G. Baraniuk, Santiago Segarra
On Local Distributions in Graph Signal Processing. IEEE Trans. Signal Process. 70 (2022)
Arindam Chowdhury, Fernando Gama, Santiago Segarra
Stability Analysis of Unfolded WMMSE for Power Allocation. ICASSP (2022)
Alejandro Parada-Mayorga, Zhiyang Wang, Fernando Gama, Alejandro Ribeiro
Stability of Aggregation Graph Neural Networks. CoRR (2022)
Fengjun Yang, Fernando Gama, Somayeh Sojoudi, Nikolai Matni
Distributed Optimal Control of Graph Symmetric Systems via Graph Filters. CoRR (2022)
Ting-Kuei Hu, Fernando Gama, Tianlong Chen, Wenqing Zheng, Zhangyang Wang, Alejandro Ribeiro, Brian M. Sadler
Scalable Perception-Action-Communication Loops With Convolutional and Graph Neural Networks. IEEE Trans. Signal Inf. Process. over Networks 8 (2022)
Elvin Isufi, Fernando Gama, David I. Shuman, Santiago Segarra
Graph Filters for Signal Processing and Machine Learning on Graphs. CoRR (2022)
Fernando Gama, Somayeh Sojoudi
Distributed linear-quadratic control with graph neural networks. Signal Process. 196 (2022)
Damian Owerko, Fernando Gama, Alejandro Ribeiro
Unsupervised Optimal Power Flow Using Graph Neural Networks. CoRR (2022)
T. Mitchell Roddenberry, Fernando Gama, Richard G. Baraniuk, Santiago Segarra
On Local Distributions in Graph Signal Processing. CoRR (2022)
Fernando Gama, Nicolas Zilberstein, Richard G. Baraniuk, Santiago Segarra
Unrolling Particles: Unsupervised Learning of Sampling Distributions. ICASSP (2022)
Arindam Chowdhury, Fernando Gama, Santiago Segarra
Stability Analysis of Unfolded WMMSE for Power Allocation. CoRR (2021)
Fernando Gama, Brendon G. Anderson, Somayeh Sojoudi
Node-Variant Graph Filters in Graph Neural Networks. CoRR (2021)
Luana Ruiz, Fernando Gama, Alejandro Ribeiro
Graph Neural Networks: Architectures, Stability, and Transferability. Proc. IEEE 109 (5) (2021)
Fernando Gama, Nicolas Zilberstein, Richard G. Baraniuk, Santiago Segarra
Unrolling Particles: Unsupervised Learning of Sampling Distributions. CoRR (2021)
Luana Ruiz, Fernando Gama, Alejandro Ribeiro, Elvin Isufi
Nonlinear State-Space Generalizations of Graph Convolutional Neural Networks. ICASSP (2021)
Zhan Gao, Alejandro Ribeiro, Fernando Gama
Wide and Deep Graph Neural Networks with Distributed Online Learning. ICASSP (2021)
Samuel Pfrommer, Alejandro Ribeiro, Fernando Gama
Discriminability of Single-Layer Graph Neural Networks. ICASSP (2021)
Ting-Kuei Hu, Fernando Gama, Tianlong Chen, Wenqing Zheng, Zhangyang Wang, Alejandro Ribeiro, Brian M. Sadler
Scalable Perception-Action-Communication Loops with Convolutional and Graph Neural Networks. CoRR (2021)
Victor M. Tenorio, Samuel Rey, Fernando Gama, Santiago Segarra, Antonio G. Marques
A Robust Alternative for Graph Convolutional Neural Networks via Graph Neighborhood Filters. CoRR (2021)
Fernando Gama, Somayeh Sojoudi
Graph Neural Networks for Distributed Linear-Quadratic Control. L4DC (2021)
Ting-Kuei Hu, Fernando Gama, Tianlong Chen, Zhangyang Wang, Alejandro Ribeiro, Brian M. Sadler
VGAI: End-to-End Learning of Vision-Based Decentralized Controllers for Robot Swarms. ICASSP (2021)
Zhan Gao, Fernando Gama, Alejandro Ribeiro
Stability of Spherical Convolutional Neural Networks to Rotation Diffeomorphisms. EUSIPCO (2021)
Fernando Gama, Ekaterina I. Tolstaya, Alejandro Ribeiro
Graph Neural Networks for Decentralized Controllers. ICASSP (2021)
Fernando Gama, Somayeh Sojoudi
Distributed Linear-Quadratic Control with Graph Neural Networks. CoRR (2021)
Zhan Gao, Fernando Gama, Alejandro Ribeiro
Wide and Deep Graph Neural Network with Distributed Online Learning. CoRR (2021)
Victor M. Tenorio, Samuel Rey, Fernando Gama, Santiago Segarra, Antonio G. Marques
A Robust Alternative for Graph Convolutional Neural Networks via Graph Neighborhood Filters. ACSCC (2021)
Zhan Gao, Fernando Gama, Alejandro Ribeiro
Spherical Convolutional Neural Networks: Stability to Perturbations in SO(3). CoRR (2020)
Elvin Isufi, Fernando Gama, Alejandro Ribeiro
EdgeNets: Edge Varying Graph Neural Networks. CoRR (2020)
Fernando Gama, Somayeh Sojoudi
Graph Neural Networks for Distributed Linear-Quadratic Control. CoRR (2020)
Ting-Kuei Hu, Fernando Gama, Zhangyang Wang, Alejandro Ribeiro, Brian M. Sadler
VGAI: A Vision-Based Decentralized Controller Learning Framework for Robot Swarms. CoRR (2020)
Qingbiao Li, Fernando Gama, Alejandro Ribeiro, Amanda Prorok
Graph Neural Networks for Decentralized Multi-Robot Path Planning. IROS (2020)
Damian Owerko, Fernando Gama, Alejandro Ribeiro
Optimal Power Flow Using Graph Neural Networks. ICASSP (2020)
Luana Ruiz, Fernando Gama, Alejandro Ribeiro
Graph Neural Networks: Architectures, Stability and Transferability. CoRR (2020)
Luana Ruiz, Fernando Gama, Alejandro Ribeiro, Elvin Isufi
Nonlinear State-Space Generalizations of Graph Convolutional Neural Networks. CoRR (2020)
Fernando Gama, Elvin Isufi, Geert Leus, Alejandro Ribeiro
Graphs, Convolutions, and Neural Networks. CoRR (2020)
Luana Ruiz, Fernando Gama, Alejandro Ribeiro
Spatial Gating Strategies for Graph Recurrent Neural Networks. ICASSP (2020)
Qingbiao Li, Fernando Gama, Alejandro Ribeiro, Amanda Prorok
Graph Neural Networks for Decentralized Path Planning. AAMAS (2020)
Zhan Gao, Fernando Gama, Alejandro Ribeiro
Wide and Deep Graph Neural Networks with Distributed Online Learning. CoRR (2020)
Fernando Gama, Alejandro Ribeiro, Joan Bruna
Stability of Graph Neural Networks to Relative Perturbations. ICASSP (2020)
Luana Ruiz, Fernando Gama, Alejandro Ribeiro
Gated Graph Recurrent Neural Networks. CoRR (2020)
Fernando Gama, Ekaterina I. Tolstaya, Alejandro Ribeiro
Graph Neural Networks for Decentralized Controllers. CoRR (2020)
Fernando Gama, Joan Bruna, Alejandro Ribeiro
Stability Properties of Graph Neural Networks. IEEE Trans. Signal Process. 68 (2020)
Fernando Gama, Antonio G. Marques, Gonzalo Mateos, Alejandro Ribeiro
Rethinking sketching as sampling: A graph signal processing approach. Signal Process. 169 (2020)
Fernando Gama, Elvin Isufi, Geert Leus, Alejandro Ribeiro
Graphs, Convolutions, and Neural Networks: From Graph Filters to Graph Neural Networks. IEEE Signal Process. Mag. 37 (6) (2020)
Luana Ruiz, Fernando Gama, Antonio Garcia Marques, Alejandro Ribeiro
Invariance-Preserving Localized Activation Functions for Graph Neural Networks. IEEE Trans. Signal Process. 68 (2020)
Fernando Gama, Qingbiao Li, Ekaterina I. Tolstaya, Amanda Prorok, Alejandro Ribeiro
Decentralized Control with Graph Neural Networks. CoRR (2020)
Samuel Pfrommer, Fernando Gama, Alejandro Ribeiro
Discriminability of Single-Layer Graph Neural Networks. CoRR (2020)
Luana Ruiz, Fernando Gama, Alejandro Ribeiro
Gated Graph Recurrent Neural Networks. IEEE Trans. Signal Process. 68 (2020)
Fernando Gama, Joan Bruna, Alejandro Ribeiro
Stability of Graph Neural Networks to Relative Perturbations. CoRR (2019)
Elvin Isufi, Fernando Gama, Alejandro Ribeiro
Generalizing Graph Convolutional Neural Networks with Edge-Variant Recursions on Graphs. CoRR (2019)
Luana Ruiz, Fernando Gama, Antonio G. Marques, Alejandro Ribeiro
Median Activation Functions for Graph Neural Networks. ICASSP (2019)
Ekaterina I. Tolstaya, Fernando Gama, James Paulos, George J. Pappas, Vijay Kumar, Alejandro Ribeiro
Learning Decentralized Controllers for Robot Swarms with Graph Neural Networks. CoRL (2019)
Damian Owerko, Fernando Gama, Alejandro Ribeiro
Optimal Power Flow Using Graph Neural Networks. CoRR (2019)
Luana Ruiz, Fernando Gama, Alejandro Ribeiro
Gated Graph Convolutional Recurrent Neural Networks. EUSIPCO (2019)
Fernando Gama, Joan Bruna, Alejandro Ribeiro
Stability of Graph Scattering Transforms. CoRR (2019)
Fernando Gama, Antonio G. Marques, Geert Leus, Alejandro Ribeiro
Convolutional Neural Network Architectures for Signals Supported on Graphs. IEEE Trans. Signal Process. 67 (4) (2019)
Fernando Gama, Antonio G. Marques, Alejandro Ribeiro, Geert Leus
Aggregation Graph Neural Networks. ICASSP (2019)
Luana Ruiz, Fernando Gama, Antonio G. Marques, Alejandro Ribeiro
Invariance-Preserving Localized Activation Functions for Graph Neural Networks. CoRR (2019)
Fernando Gama, Joan Bruna, Alejandro Ribeiro
Stability Properties of Graph Neural Networks. CoRR (2019)
Fernando Gama, Alejandro Ribeiro, Joan Bruna
Diffusion Scattering Transforms on Graphs. ICLR (Poster) (2019)
Fernando Gama, Elvin Isufi, Alejandro Ribeiro, Geert Leus
Controllability of Bandlimited Graph Processes Over Random Time Varying Graphs. IEEE Trans. Signal Process. 67 (24) (2019)
Qingbiao Li, Fernando Gama, Alejandro Ribeiro, Amanda Prorok
Graph Neural Networks for Decentralized Multi-Robot Path Planning. CoRR (2019)
Fernando Gama, Alejandro Ribeiro
Ergodicity in Stationary Graph Processes: A Weak Law of Large Numbers. IEEE Trans. Signal Process. 67 (10) (2019)
Mario Coutino, Elvin Isufi, Fernando Gama, Alejandro Ribeiro, Geert Leus
Design Strategies for Sparse Control Of Random Time-Varying NETWORKS. ACSSC (2019)
Fernando Gama, Antonio G. Marques, Geert Leus, Alejandro Ribeiro
Convolutional Graph Neural Networks. ACSSC (2019)
Ekaterina I. Tolstaya, Fernando Gama, James Paulos, George J. Pappas, Vijay Kumar, Alejandro Ribeiro
Learning Decentralized Controllers for Robot Swarms with Graph Neural Networks. CoRR (2019)
Fernando Gama, Alejandro Ribeiro, Joan Bruna
Stability of Graph Scattering Transforms. NeurIPS (2019)
Luana Ruiz, Fernando Gama, Alejandro Ribeiro
Gated Graph Convolutional Recurrent Neural Networks. CoRR (2019)
Fernando Gama, Elvin Isufi, Alejandro Ribeiro, Geert Leus
Controllability of Bandlimited Graph Processes Over Random Time-Varying Graphs. CoRR (2019)
Elvin Isufi, Fernando Gama, Alejandro Ribeiro
Generalizing Graph Convolutional Neural Networks with Edge-Variant Recursions on Graphs. EUSIPCO (2019)
Fernando Gama, Antonio G. Marques, Alejandro Ribeiro, Geert Leus
MIMO Graph Filters for Convolutional Neural Networks. CoRR (2018)
Fernando Gama, Santiago Segarra, Alejandro Ribeiro
Hierarchical Overlapping Clustering of Network Data Using Cut Metrics. IEEE Trans. Signal Inf. Process. over Networks 4 (2) (2018)
Fernando Gama, Alejandro Ribeiro, Joan Bruna
Diffusion Scattering Transforms on Graphs. CoRR (2018)
Fernando Gama, Antonio G. Marques, Alejandro Ribeiro, Geert Leus
MIMO Graph Filters for Convolutional Neural Networks. SPAWC (2018)
Fernando Gama, Antonio G. Marques, Geert Leus, Alejandro Ribeiro
CNN Architectures for Graph Data. GlobalSIP (2018)
Fernando Gama, Elvin Isufi, Geert Leus, Alejandro Ribeiro
Control of Graph Signals Over Random Time-Varying Graphs. ICASSP (2018)
Fernando Gama, Antonio G. Marques, Geert Leus, Alejandro Ribeiro
Convolutional Neural Networks Architectures for Signals Supported on Graphs. CoRR (2018)
Damian Owerko, Fernando Gama, Alejandro Ribeiro
Predicting Power Outages Using Graph Neural Networks. GlobalSIP (2018)
Fernando Gama, Geert Leus, Antonio G. Marques, Alejandro Ribeiro
Convolutional Neural Networks via Node-Varying Graph Filters. DSW (2018)
Luana Ruiz, Fernando Gama, Antonio G. Marques, Alejandro Ribeiro
Median activation functions for graph neural networks. CoRR (2018)
Fernando Gama, Alejandro Ribeiro
Distributed estimation of smooth graph power spectral density. GlobalSIP (2017)
Fernando Gama, Helder M. Arruda, Hanna V. Carvalho, Paulo A. de Souza, Gustavo Pessin
Improving Our Understanding of the Behavior of Bees Through Anomaly Detection Techniques. ICANN (2) (2017)
Fernando Gama, Geert Leus, Antonio Garcia Marques, Alejandro Ribeiro
Convolutional Neural Networks Via Node-Varying Graph Filters. CoRR (2017)
Fernando Gama, Alejandro Ribeiro
Weak law of large numbers for stationary graph processes. ICASSP (2017)
Wallace P. Lira, Fernando Gama, Hivana Melo Barbosa Dall'Agnol, Ronnie Alves, Cleidson R. B. de Souza
VCloud: adding interactiveness to word clouds for knowledge exploration in large unstructured texts. SAC (2016)
Fernando Gama, Santiago Segarra, Alejandro Ribeiro
Overlapping clustering of network data using cut metrics. ICASSP (2016)
Fernando Gama, Antonio G. Marques, Gonzalo Mateos, Alejandro Ribeiro
Rethinking sketching as sampling: Linear transforms of graph signals. ACSSC (2016)
Fernando Gama, Antonio G. Marques, Gonzalo Mateos, Alejandro Ribeiro
Rethinking Sketching as Sampling: A Graph Signal Processing Approach. CoRR (2016)
Fernando Gama, Santiago Segarra, Alejandro Ribeiro
Hierarchical Overlapping Clustering of Network Data Using Cut Metrics. CoRR (2016)
Fernando Gama, Daniel Casaglia, Bruno Cernuschi-Frías
Analysis and Comparison of Biased Affine Estimators. IEEE Trans. Signal Process. 63 (4) (2015)
Bruno Cernuschi-Frías, Fernando Gama, Daniel Casaglia
Deepest Minimum Criterion for Biased Affine Estimation. IEEE Trans. Signal Process. 62 (9) (2014)