Fernando Gama

According to our database, Fernando Gama authored at least 65 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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

Stability of Aggregation Graph Neural Networks.

Alejandro Parada-Mayorga, Zhiyang Wang, Fernando Gama, Alejandro Ribeiro

IEEE Trans. Signal Inf. Process. over Networks, 2023

Distributed Power System State Estimation Using Graph Convolutional Neural Networks.

Sangwoo Park, Fernando Gama, Javad Lavaei, Somayeh Sojoudi

Proceedings of the 56th Hawaii International Conference on System Sciences, 2023

2022

On Local Distributions in Graph Signal Processing.

T. Mitchell Roddenberry, Fernando Gama, Richard G. Baraniuk, Santiago Segarra

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

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

Scalable Perception-Action-Communication Loops With Convolutional and Graph Neural Networks.

Ting-Kuei Hu, Fernando Gama, Tianlong Chen, Wenqing Zheng, Zhangyang Wang, Alejandro Ribeiro, Brian M. Sadler

IEEE Trans. Signal Inf. Process. over Networks, 2022

Spherical convolutional neural networks: Stability to perturbations in SO(3).

Zhan Gao, Fernando Gama, Alejandro Ribeiro

Signal Process., 2022

Distributed linear-quadratic control with graph neural networks.

Fernando Gama, Somayeh Sojoudi

Signal Process., 2022

EdgeNets: Edge Varying Graph Neural Networks.

Elvin Isufi, Fernando Gama, Alejandro Ribeiro

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Graph Filters for Signal Processing and Machine Learning on Graphs.

Elvin Isufi, Fernando Gama, David I. Shuman, Santiago Segarra

CoRR, 2022

Unsupervised Optimal Power Flow Using Graph Neural Networks.

Damian Owerko, Fernando Gama, Alejandro Ribeiro

CoRR, 2022

Unrolling Particles: Unsupervised Learning of Sampling Distributions.

Fernando Gama, Nicolas Zilberstein, Richard G. Baraniuk, Santiago Segarra

Proceedings of the IEEE International Conference on Acoustics, 2022

Stability Analysis of Unfolded WMMSE for Power Allocation.

Arindam Chowdhury, Fernando Gama, Santiago Segarra

Proceedings of the IEEE International Conference on Acoustics, 2022

Distributed Optimal Control of Graph Symmetric Systems via Graph Filters.

Fengjun Yang, Fernando Gama, Somayeh Sojoudi, Nikolai Matni

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

2021

Graph Neural Networks: Architectures, Stability, and Transferability.

Luana Ruiz, Fernando Gama, Alejandro Ribeiro

Proc. IEEE, 2021

Node-Variant Graph Filters in Graph Neural Networks.

Fernando Gama, Brendon G. Anderson, Somayeh Sojoudi

CoRR, 2021

Graph Neural Networks for Distributed Linear-Quadratic Control.

Fernando Gama, Somayeh Sojoudi

Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Nonlinear State-Space Generalizations of Graph Convolutional Neural Networks.

Luana Ruiz, Fernando Gama, Alejandro Ribeiro, Elvin Isufi

Proceedings of the IEEE International Conference on Acoustics, 2021

Discriminability of Single-Layer Graph Neural Networks.

Samuel Pfrommer, Alejandro Ribeiro, Fernando Gama

Proceedings of the IEEE International Conference on Acoustics, 2021

VGAI: End-to-End Learning of Vision-Based Decentralized Controllers for Robot Swarms.

Ting-Kuei Hu, Fernando Gama, Tianlong Chen, Zhangyang Wang, Alejandro Ribeiro, Brian M. Sadler

Proceedings of the IEEE International Conference on Acoustics, 2021

Wide and Deep Graph Neural Networks with Distributed Online Learning.

Zhan Gao, Alejandro Ribeiro, Fernando Gama

Proceedings of the IEEE International Conference on Acoustics, 2021

Graph Neural Networks for Decentralized Controllers.

Fernando Gama, Ekaterina I. Tolstaya, Alejandro Ribeiro

Proceedings of the IEEE International Conference on Acoustics, 2021

Stability of Spherical Convolutional Neural Networks to Rotation Diffeomorphisms.

Zhan Gao, Fernando Gama, Alejandro Ribeiro

Proceedings of the 29th European Signal Processing Conference, 2021

A Robust Alternative for Graph Convolutional Neural Networks via Graph Neighborhood Filters.

Victor M. Tenorio, Samuel Rey, Fernando Gama, Santiago Segarra, Antonio G. Marques

Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021

2020

Gated Graph Recurrent Neural Networks.

Luana Ruiz, Fernando Gama, 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

Stability Properties of Graph Neural Networks.

Fernando Gama, Joan Bruna, Alejandro Ribeiro

IEEE Trans. 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

Rethinking sketching as sampling: A graph signal processing approach.

Fernando Gama, Antonio G. Marques, Gonzalo Mateos, Alejandro Ribeiro

Signal Process., 2020

Decentralized Control with Graph Neural Networks.

Fernando Gama, Qingbiao Li, Ekaterina I. Tolstaya, Amanda Prorok, Alejandro Ribeiro

CoRR, 2020

Graphs, Convolutions, and Neural Networks.

Fernando Gama, Elvin Isufi, Geert Leus, Alejandro Ribeiro

CoRR, 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

Graph Neural Networks for Decentralized Multi-Robot Path Planning.

Qingbiao Li, Fernando Gama, Alejandro Ribeiro, Amanda Prorok

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Spatial Gating Strategies for Graph Recurrent Neural Networks.

Luana Ruiz, Fernando Gama, Alejandro Ribeiro

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Optimal Power Flow Using Graph Neural Networks.

Damian Owerko, Fernando Gama, Alejandro Ribeiro

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Stability of Graph Neural Networks to Relative Perturbations.

Fernando Gama, Alejandro Ribeiro, Joan Bruna

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Graph Neural Networks for Decentralized Path Planning.

Qingbiao Li, Fernando Gama, Alejandro Ribeiro, Amanda Prorok

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019

Ergodicity in Stationary Graph Processes: A Weak Law of Large Numbers.

Fernando Gama, Alejandro Ribeiro

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

Controllability of Bandlimited Graph Processes Over Random Time Varying Graphs.

Fernando Gama, Elvin Isufi, Alejandro Ribeiro, Geert Leus

IEEE Trans. Signal Process., 2019

Stability of Graph Scattering Transforms.

Fernando Gama, Alejandro Ribeiro, Joan Bruna

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Diffusion Scattering Transforms on Graphs.

Fernando Gama, Alejandro Ribeiro, Joan Bruna

Proceedings of the 7th International Conference on Learning Representations, 2019

Median Activation Functions for Graph Neural Networks.

Luana Ruiz, Fernando Gama, Antonio G. Marques, Alejandro Ribeiro

Proceedings of the IEEE International Conference on Acoustics, 2019

Aggregation Graph Neural Networks.

Fernando Gama, Antonio G. Marques, Alejandro Ribeiro, Geert Leus

Proceedings of the IEEE International Conference on Acoustics, 2019

Gated Graph Convolutional Recurrent Neural Networks.

Luana Ruiz, Fernando Gama, Alejandro Ribeiro

Proceedings of the 27th European Signal Processing Conference, 2019

Generalizing Graph Convolutional Neural Networks with Edge-Variant Recursions on Graphs.

Elvin Isufi, Fernando Gama, Alejandro Ribeiro

Proceedings of the 27th European Signal Processing Conference, 2019

Learning Decentralized Controllers for Robot Swarms with Graph Neural Networks.

Ekaterina I. Tolstaya, Fernando Gama, James Paulos, George J. Pappas, Vijay Kumar, Alejandro Ribeiro

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

Convolutional Graph Neural Networks.

Fernando Gama, Antonio G. Marques, Geert Leus, Alejandro Ribeiro

Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

Design Strategies for Sparse Control Of Random Time-Varying NETWORKS.

Mario Coutino, Elvin Isufi, Fernando Gama, Alejandro Ribeiro, Geert Leus

Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018

Hierarchical Overlapping Clustering of Network Data Using Cut Metrics.

Fernando Gama, Santiago Segarra, Alejandro Ribeiro

IEEE Trans. Signal Inf. Process. over Networks, 2018

Convolutional Neural Networks Architectures for Signals Supported on Graphs.

Fernando Gama, Antonio G. Marques, Geert Leus, Alejandro Ribeiro

CoRR, 2018

MIMO Graph Filters for Convolutional Neural Networks.

Fernando Gama, Antonio G. Marques, Alejandro Ribeiro, Geert Leus

Proceedings of the 19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2018

Control of Graph Signals Over Random Time-Varying Graphs.

Fernando Gama, Elvin Isufi, Geert Leus, Alejandro Ribeiro

Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Predicting Power Outages Using Graph Neural Networks.

Damian Owerko, Fernando Gama, Alejandro Ribeiro

Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018

CNN Architectures for Graph Data.

Fernando Gama, Antonio G. Marques, Geert Leus, Alejandro Ribeiro

Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018

Convolutional Neural Networks via Node-Varying Graph Filters.

Fernando Gama, Geert Leus, Antonio G. Marques, Alejandro Ribeiro

Proceedings of the 2018 IEEE Data Science Workshop, 2018

2017

Weak law of large numbers for stationary graph processes.

Fernando Gama, Alejandro Ribeiro

Proceedings of the 2017 IEEE International Conference on Acoustics, 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

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2017, 2017

Distributed estimation of smooth graph power spectral density.

Fernando Gama, Alejandro Ribeiro

Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017

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

Proceedings of the 31st Annual ACM Symposium on Applied Computing, 2016

Overlapping clustering of network data using cut metrics.

Fernando Gama, Santiago Segarra, Alejandro Ribeiro

Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Rethinking sketching as sampling: Linear transforms of graph signals.

Fernando Gama, Antonio G. Marques, Gonzalo Mateos, Alejandro Ribeiro

Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016

2015

Analysis and Comparison of Biased Affine Estimators.

Fernando Gama, Daniel Casaglia, Bruno Cernuschi-Frías

IEEE Trans. Signal Process., 2015

2014

Deepest Minimum Criterion for Biased Affine Estimation.

Bruno Cernuschi-Frías, Fernando Gama, Daniel Casaglia

IEEE Trans. Signal Process., 2014