Fernando Gama

Orcid: 0000-0001-6117-8193

According to our database1, Fernando Gama authored at least 66 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Distributed UAV Beamforming Using Graph Recurrent Neural Networks.
Proceedings of the 13th IEEE Sensor Array and Multichannel Signal Processing Workshop, 2024

Unsupervised Optimal Power Flow Using Graph Neural Networks.
Proceedings of the IEEE International Conference on Acoustics, 2024

2023
Unsupervised Learning of Sampling Distributions for Particle Filters.
IEEE Trans. Signal Process., 2023

Stability of Aggregation Graph Neural Networks.
IEEE Trans. Signal Inf. Process. over Networks, 2023

Distributed Power System State Estimation Using Graph Convolutional Neural Networks.
Proceedings of the 56th Hawaii International Conference on System Sciences, 2023

2022
On Local Distributions in Graph Signal Processing.
IEEE Trans. Signal Process., 2022

Wide and Deep Graph Neural Network With Distributed Online Learning.
IEEE Trans. Signal Process., 2022

Synthesizing Decentralized Controllers With Graph Neural Networks and Imitation Learning.
IEEE Trans. Signal Process., 2022

Scalable Perception-Action-Communication Loops With Convolutional and Graph Neural Networks.
IEEE Trans. Signal Inf. Process. over Networks, 2022

Spherical convolutional neural networks: Stability to perturbations in SO(3).
Signal Process., 2022

Distributed linear-quadratic control with graph neural networks.
Signal Process., 2022

EdgeNets: Edge Varying Graph Neural Networks.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Graph Filters for Signal Processing and Machine Learning on Graphs.
CoRR, 2022

Unrolling Particles: Unsupervised Learning of Sampling Distributions.
Proceedings of the IEEE International Conference on Acoustics, 2022

Stability Analysis of Unfolded WMMSE for Power Allocation.
Proceedings of the IEEE International Conference on Acoustics, 2022

Distributed Optimal Control of Graph Symmetric Systems via Graph Filters.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022

2021
Graph Neural Networks: Architectures, Stability, and Transferability.
Proc. IEEE, 2021

Node-Variant Graph Filters in Graph Neural Networks.
CoRR, 2021

Graph Neural Networks for Distributed Linear-Quadratic Control.
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Nonlinear State-Space Generalizations of Graph Convolutional Neural Networks.
Proceedings of the IEEE International Conference on Acoustics, 2021

Discriminability of Single-Layer Graph Neural Networks.
Proceedings of the IEEE International Conference on Acoustics, 2021

VGAI: End-to-End Learning of Vision-Based Decentralized Controllers for Robot Swarms.
Proceedings of the IEEE International Conference on Acoustics, 2021

Wide and Deep Graph Neural Networks with Distributed Online Learning.
Proceedings of the IEEE International Conference on Acoustics, 2021

Graph Neural Networks for Decentralized Controllers.
Proceedings of the IEEE International Conference on Acoustics, 2021

Stability of Spherical Convolutional Neural Networks to Rotation Diffeomorphisms.
Proceedings of the 29th European Signal Processing Conference, 2021

A Robust Alternative for Graph Convolutional Neural Networks via Graph Neighborhood Filters.
Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021

2020
Gated Graph Recurrent Neural Networks.
IEEE Trans. Signal Process., 2020

Invariance-Preserving Localized Activation Functions for Graph Neural Networks.
IEEE Trans. Signal Process., 2020

Stability Properties of Graph Neural Networks.
IEEE Trans. Signal Process., 2020

Graphs, Convolutions, and Neural Networks: From Graph Filters to Graph Neural Networks.
IEEE Signal Process. Mag., 2020

Rethinking sketching as sampling: A graph signal processing approach.
Signal Process., 2020

Decentralized Control with Graph Neural Networks.
CoRR, 2020

Graphs, Convolutions, and Neural Networks.
CoRR, 2020

VGAI: A Vision-Based Decentralized Controller Learning Framework for Robot Swarms.
CoRR, 2020

Graph Neural Networks for Decentralized Multi-Robot Path Planning.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Spatial Gating Strategies for Graph Recurrent Neural Networks.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Optimal Power Flow Using Graph Neural Networks.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Stability of Graph Neural Networks to Relative Perturbations.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Graph Neural Networks for Decentralized Path Planning.
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.
IEEE Trans. Signal Process., 2019

Convolutional Neural Network Architectures for Signals Supported on Graphs.
IEEE Trans. Signal Process., 2019

Controllability of Bandlimited Graph Processes Over Random Time Varying Graphs.
IEEE Trans. Signal Process., 2019

Stability of Graph Scattering Transforms.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Diffusion Scattering Transforms on Graphs.
Proceedings of the 7th International Conference on Learning Representations, 2019

Median Activation Functions for Graph Neural Networks.
Proceedings of the IEEE International Conference on Acoustics, 2019

Aggregation Graph Neural Networks.
Proceedings of the IEEE International Conference on Acoustics, 2019

Gated Graph Convolutional Recurrent Neural Networks.
Proceedings of the 27th European Signal Processing Conference, 2019

Generalizing Graph Convolutional Neural Networks with Edge-Variant Recursions on Graphs.
Proceedings of the 27th European Signal Processing Conference, 2019

Learning Decentralized Controllers for Robot Swarms with Graph Neural Networks.
Proceedings of the 3rd Annual Conference on Robot Learning, 2019

Convolutional Graph Neural Networks.
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

Design Strategies for Sparse Control Of Random Time-Varying NETWORKS.
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018
Hierarchical Overlapping Clustering of Network Data Using Cut Metrics.
IEEE Trans. Signal Inf. Process. over Networks, 2018

Convolutional Neural Networks Architectures for Signals Supported on Graphs.
CoRR, 2018

MIMO Graph Filters for Convolutional Neural Networks.
Proceedings of the 19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2018

Control of Graph Signals Over Random Time-Varying Graphs.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Predicting Power Outages Using Graph Neural Networks.
Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018

CNN Architectures for Graph Data.
Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018

Convolutional Neural Networks via Node-Varying Graph Filters.
Proceedings of the 2018 IEEE Data Science Workshop, 2018

2017
Weak law of large numbers for stationary graph processes.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Improving Our Understanding of the Behavior of Bees Through Anomaly Detection Techniques.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2017, 2017

Distributed estimation of smooth graph power spectral density.
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.
Proceedings of the 31st Annual ACM Symposium on Applied Computing, 2016

Overlapping clustering of network data using cut metrics.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Rethinking sketching as sampling: Linear transforms of graph signals.
Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016

2015
Analysis and Comparison of Biased Affine Estimators.
IEEE Trans. Signal Process., 2015

2014
Deepest Minimum Criterion for Biased Affine Estimation.
IEEE Trans. Signal Process., 2014


  Loading...