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Fernando Gama
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2020 – today
- 2024
- [j22]Elvin Isufi
, Fernando Gama
Graph Filters for Signal Processing and Machine Learning on Graphs. IEEE Trans. Signal Process. 72: 4745-4781 (2024) - [c39]Damian Owerko, Fernando Gama, Alejandro Ribeiro:
Unsupervised Optimal Power Flow Using Graph Neural Networks. ICASSP 2024: 6885-6889 - [c38]Wenqing Zheng, Brian M. Sadler, Fernando Gama, Tianlong Chen:
Distributed UAV Beamforming Using Graph Recurrent Neural Networks. SAM 2024: 1-5 - 2023
- [j21]Alejandro Parada-Mayorga
Stability of Aggregation Graph Neural Networks. IEEE Trans. Signal Inf. Process. over Networks 9: 850-864 (2023) - [j20]Fernando Gama
Unsupervised Learning of Sampling Distributions for Particle Filters. IEEE Trans. Signal Process. 71: 3852-3866 (2023) - [c37]Sangwoo Park, Fernando Gama, Javad Lavaei, Somayeh Sojoudi:
Distributed Power System State Estimation Using Graph Convolutional Neural Networks. HICSS 2023: 2756-2765 - 2022
- [j19]Elvin Isufi
EdgeNets: Edge Varying Graph Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. 44(11): 7457-7473 (2022) - [j18]Fernando Gama
Distributed linear-quadratic control with graph neural networks. Signal Process. 196: 108506 (2022) - [j17]Zhan Gao
Spherical convolutional neural networks: Stability to perturbations in SO(3). Signal Process. 196: 108529 (2022) - [j16]Ting-Kuei Hu, Fernando Gama
Scalable Perception-Action-Communication Loops With Convolutional and Graph Neural Networks. IEEE Trans. Signal Inf. Process. over Networks 8: 12-24 (2022) - [j15]Fernando Gama
Synthesizing Decentralized Controllers With Graph Neural Networks and Imitation Learning. IEEE Trans. Signal Process. 70: 1932-1946 (2022) - [j14]Zhan Gao
Wide and Deep Graph Neural Network With Distributed Online Learning. IEEE Trans. Signal Process. 70: 3862-3877 (2022) - [j13]T. Mitchell Roddenberry
On Local Distributions in Graph Signal Processing. IEEE Trans. Signal Process. 70: 5564-5577 (2022) - [c36]Fengjun Yang, Fernando Gama, Somayeh Sojoudi, Nikolai Matni:
Distributed Optimal Control of Graph Symmetric Systems via Graph Filters. CDC 2022: 5245-5252 - [c35]Arindam Chowdhury, Fernando Gama, Santiago Segarra
Stability Analysis of Unfolded WMMSE for Power Allocation. ICASSP 2022: 5298-5302 - [c34]Fernando Gama, Nicolas Zilberstein, Richard G. Baraniuk, Santiago Segarra
Unrolling Particles: Unsupervised Learning of Sampling Distributions. ICASSP 2022: 5498-5502 - [i41]T. Mitchell Roddenberry, Fernando Gama, Richard G. Baraniuk, Santiago Segarra:
On Local Distributions in Graph Signal Processing. CoRR abs/2202.10649 (2022) - [i40]Alejandro Parada-Mayorga, Zhiyang Wang, Fernando Gama, Alejandro Ribeiro:
Stability of Aggregation Graph Neural Networks. CoRR abs/2207.03678 (2022) - [i39]Damian Owerko, Fernando Gama, Alejandro Ribeiro:
Unsupervised Optimal Power Flow Using Graph Neural Networks. CoRR abs/2210.09277 (2022) - [i38]Fengjun Yang, Fernando Gama, Somayeh Sojoudi, Nikolai Matni:
Distributed Optimal Control of Graph Symmetric Systems via Graph Filters. CoRR abs/2210.15847 (2022) - [i37]Elvin Isufi, Fernando Gama, David I. Shuman, Santiago Segarra
Graph Filters for Signal Processing and Machine Learning on Graphs. CoRR abs/2211.08854 (2022) - 2021
- [j12]Luana Ruiz
Graph Neural Networks: Architectures, Stability, and Transferability. Proc. IEEE 109(5): 660-682 (2021) - [c33]Victor M. Tenorio
A Robust Alternative for Graph Convolutional Neural Networks via Graph Neighborhood Filters. ACSCC 2021: 1573-1578 - [c32]Zhan Gao, Fernando Gama, Alejandro Ribeiro
Stability of Spherical Convolutional Neural Networks to Rotation Diffeomorphisms. EUSIPCO 2021: 1451-1455 - [c31]Ting-Kuei Hu, Fernando Gama, Tianlong Chen, Zhangyang Wang, Alejandro Ribeiro
VGAI: End-to-End Learning of Vision-Based Decentralized Controllers for Robot Swarms. ICASSP 2021: 4900-4904 - [c30]Fernando Gama, Ekaterina I. Tolstaya, Alejandro Ribeiro
Graph Neural Networks for Decentralized Controllers. ICASSP 2021: 5260-5264 - [c29]Luana Ruiz, Fernando Gama, Alejandro Ribeiro
Nonlinear State-Space Generalizations of Graph Convolutional Neural Networks. ICASSP 2021: 5265-5269 - [c28]Zhan Gao, Alejandro Ribeiro
Wide and Deep Graph Neural Networks with Distributed Online Learning. ICASSP 2021: 5270-5274 - [c27]Samuel Pfrommer, Alejandro Ribeiro
Discriminability of Single-Layer Graph Neural Networks. ICASSP 2021: 8508-8512 - [c26]Fernando Gama, Somayeh Sojoudi:
Graph Neural Networks for Distributed Linear-Quadratic Control. L4DC 2021: 111-124 - [i36]Fernando Gama, Somayeh Sojoudi:
Distributed Linear-Quadratic Control with Graph Neural Networks. CoRR abs/2103.08417 (2021) - [i35]Fernando Gama, Brendon G. Anderson, Somayeh Sojoudi:
Node-Variant Graph Filters in Graph Neural Networks. CoRR abs/2106.00089 (2021) - [i34]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 abs/2106.13358 (2021) - [i33]Zhan Gao, Fernando Gama, Alejandro Ribeiro:
Wide and Deep Graph Neural Network with Distributed Online Learning. CoRR abs/2107.09203 (2021) - [i32]Victor M. Tenorio, Samuel Rey
A Robust Alternative for Graph Convolutional Neural Networks via Graph Neighborhood Filters. CoRR abs/2110.00844 (2021) - [i31]Fernando Gama, Nicolas Zilberstein, Richard G. Baraniuk, Santiago Segarra:
Unrolling Particles: Unsupervised Learning of Sampling Distributions. CoRR abs/2110.02915 (2021) - [i30]Arindam Chowdhury, Fernando Gama, Santiago Segarra:
Stability Analysis of Unfolded WMMSE for Power Allocation. CoRR abs/2110.07471 (2021) - 2020
- [j11]Fernando Gama
Rethinking sketching as sampling: A graph signal processing approach. Signal Process. 169: 107404 (2020) - [j10]Fernando Gama
Graphs, Convolutions, and Neural Networks: From Graph Filters to Graph Neural Networks. IEEE Signal Process. Mag. 37(6): 128-138 (2020) - [j9]Luana Ruiz
Invariance-Preserving Localized Activation Functions for Graph Neural Networks. IEEE Trans. Signal Process. 68: 127-141 (2020) - [j8]Fernando Gama
Stability Properties of Graph Neural Networks. IEEE Trans. Signal Process. 68: 5680-5695 (2020) - [j7]Luana Ruiz
Gated Graph Recurrent Neural Networks. IEEE Trans. Signal Process. 68: 6303-6318 (2020) - [c25]Qingbiao Li, Fernando Gama, Alejandro Ribeiro, Amanda Prorok:
Graph Neural Networks for Decentralized Path Planning. AAMAS 2020: 1901-1903 - [c24]Luana Ruiz, Fernando Gama, Alejandro Ribeiro
Spatial Gating Strategies for Graph Recurrent Neural Networks. ICASSP 2020: 5550-5554 - [c23]Damian Owerko
Optimal Power Flow Using Graph Neural Networks. ICASSP 2020: 5930-5934 - [c22]Fernando Gama, Alejandro Ribeiro
Stability of Graph Neural Networks to Relative Perturbations. ICASSP 2020: 9070-9074 - [c21]Qingbiao Li, Fernando Gama, Alejandro Ribeiro
Graph Neural Networks for Decentralized Multi-Robot Path Planning. IROS 2020: 11785-11792 - [i29]Elvin Isufi, Fernando Gama, Alejandro Ribeiro:
EdgeNets: Edge Varying Graph Neural Networks. CoRR abs/2001.07620 (2020) - [i28]Luana Ruiz, Fernando Gama, Alejandro Ribeiro:
Gated Graph Recurrent Neural Networks. CoRR abs/2002.01038 (2020) - [i27]Ting-Kuei Hu, Fernando Gama, Zhangyang Wang, Alejandro Ribeiro, Brian M. Sadler:
VGAI: A Vision-Based Decentralized Controller Learning Framework for Robot Swarms. CoRR abs/2002.02308 (2020) - [i26]Fernando Gama, Elvin Isufi, Geert Leus, Alejandro Ribeiro:
Graphs, Convolutions, and Neural Networks. CoRR abs/2003.03777 (2020) - [i25]Fernando Gama, Ekaterina I. Tolstaya, Alejandro Ribeiro:
Graph Neural Networks for Decentralized Controllers. CoRR abs/2003.10280 (2020) - [i24]Zhan Gao, Fernando Gama, Alejandro Ribeiro:
Wide and Deep Graph Neural Networks with Distributed Online Learning. CoRR abs/2006.06376 (2020) - [i23]Luana Ruiz, Fernando Gama, Alejandro Ribeiro:
Graph Neural Networks: Architectures, Stability and Transferability. CoRR abs/2008.01767 (2020) - [i22]Zhan Gao, Fernando Gama, Alejandro Ribeiro:
Spherical Convolutional Neural Networks: Stability to Perturbations in SO(3). CoRR abs/2010.05865 (2020) - [i21]Samuel Pfrommer, Fernando Gama, Alejandro Ribeiro:
Discriminability of Single-Layer Graph Neural Networks. CoRR abs/2010.08847 (2020) - [i20]Luana Ruiz, Fernando Gama, Alejandro Ribeiro, Elvin Isufi:
Nonlinear State-Space Generalizations of Graph Convolutional Neural Networks. CoRR abs/2010.14585 (2020) - [i19]Fernando Gama, Somayeh Sojoudi:
Graph Neural Networks for Distributed Linear-Quadratic Control. CoRR abs/2011.05360 (2020) - [i18]Fernando Gama, Qingbiao Li, Ekaterina I. Tolstaya, Amanda Prorok, Alejandro Ribeiro:
Decentralized Control with Graph Neural Networks. CoRR abs/2012.14906 (2020)
2010 – 2019
- 2019
- [j6]Fernando Gama
Convolutional Neural Network Architectures for Signals Supported on Graphs. IEEE Trans. Signal Process. 67(4): 1034-1049 (2019) - [j5]Fernando Gama
Ergodicity in Stationary Graph Processes: A Weak Law of Large Numbers. IEEE Trans. Signal Process. 67(10): 2761-2774 (2019) - [j4]Fernando Gama
Controllability of Bandlimited Graph Processes Over Random Time Varying Graphs. IEEE Trans. Signal Process. 67(24): 6440-6454 (2019) - [c20]Mario Coutino, Elvin Isufi, Fernando Gama, Alejandro Ribeiro, Geert Leus:
Design Strategies for Sparse Control Of Random Time-Varying NETWORKS. ACSSC 2019: 184-188 - [c19]Fernando Gama, Antonio G. Marques
Convolutional Graph Neural Networks. ACSSC 2019: 452-456 - [c18]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: 671-682 - [c17]Elvin Isufi, Fernando Gama, Alejandro Ribeiro:
Generalizing Graph Convolutional Neural Networks with Edge-Variant Recursions on Graphs. EUSIPCO 2019: 1-5 - [c16]Luana Ruiz, Fernando Gama, Alejandro Ribeiro:
Gated Graph Convolutional Recurrent Neural Networks. EUSIPCO 2019: 1-5 - [c15]Fernando Gama, Antonio G. Marques
Aggregation Graph Neural Networks. ICASSP 2019: 4943-4947 - [c14]Luana Ruiz, Fernando Gama, Antonio G. Marques
Median Activation Functions for Graph Neural Networks. ICASSP 2019: 7440-7444 - [c13]Fernando Gama, Alejandro Ribeiro, Joan Bruna:
Diffusion Scattering Transforms on Graphs. ICLR (Poster) 2019 - [c12]Fernando Gama, Alejandro Ribeiro, Joan Bruna:
Stability of Graph Scattering Transforms. NeurIPS 2019: 8036-8046 - [i17]Elvin Isufi, Fernando Gama, Alejandro Ribeiro:
Generalizing Graph Convolutional Neural Networks with Edge-Variant Recursions on Graphs. CoRR abs/1903.01298 (2019) - [i16]Luana Ruiz, Fernando Gama, Alejandro Ribeiro:
Gated Graph Convolutional Recurrent Neural Networks. CoRR abs/1903.01888 (2019) - [i15]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 abs/1903.10527 (2019) - [i14]Luana Ruiz, Fernando Gama, Antonio G. Marques, Alejandro Ribeiro:
Invariance-Preserving Localized Activation Functions for Graph Neural Networks. CoRR abs/1903.12575 (2019) - [i13]Fernando Gama, Elvin Isufi, Alejandro Ribeiro, Geert Leus:
Controllability of Bandlimited Graph Processes Over Random Time-Varying Graphs. CoRR abs/1904.10089 (2019) - [i12]Fernando Gama, Joan Bruna, Alejandro Ribeiro:
Stability Properties of Graph Neural Networks. CoRR abs/1905.04497 (2019) - [i11]Fernando Gama, Joan Bruna, Alejandro Ribeiro:
Stability of Graph Scattering Transforms. CoRR abs/1906.04784 (2019) - [i10]Fernando Gama, Joan Bruna, Alejandro Ribeiro:
Stability of Graph Neural Networks to Relative Perturbations. CoRR abs/1910.09655 (2019) - [i9]Damian Owerko, Fernando Gama, Alejandro Ribeiro:
Optimal Power Flow Using Graph Neural Networks. CoRR abs/1910.09658 (2019) - [i8]Qingbiao Li, Fernando Gama, Alejandro Ribeiro, Amanda Prorok:
Graph Neural Networks for Decentralized Multi-Robot Path Planning. CoRR abs/1912.06095 (2019) - 2018
- [j3]Fernando Gama
Hierarchical Overlapping Clustering of Network Data Using Cut Metrics. IEEE Trans. Signal Inf. Process. over Networks 4(2): 392-406 (2018) - [c11]Fernando Gama, Geert Leus
Convolutional Neural Networks via Node-Varying Graph Filters. DSW 2018: 220-224 - [c10]Fernando Gama, Antonio G. Marques
CNN Architectures for Graph Data. GlobalSIP 2018: 723-724 - [c9]Damian Owerko
Predicting Power Outages Using Graph Neural Networks. GlobalSIP 2018: 743-747 - [c8]Fernando Gama, Elvin Isufi, Geert Leus
Control of Graph Signals Over Random Time-Varying Graphs. ICASSP 2018: 4169-4173 - [c7]Fernando Gama, Antonio G. Marques
MIMO Graph Filters for Convolutional Neural Networks. SPAWC 2018: 1-5 - [i7]Fernando Gama, Antonio G. Marques, Alejandro Ribeiro, Geert Leus:
MIMO Graph Filters for Convolutional Neural Networks. CoRR abs/1803.02247 (2018) - [i6]Fernando Gama, Antonio G. Marques, Geert Leus, Alejandro Ribeiro:
Convolutional Neural Networks Architectures for Signals Supported on Graphs. CoRR abs/1805.00165 (2018) - [i5]Fernando Gama, Alejandro Ribeiro, Joan Bruna:
Diffusion Scattering Transforms on Graphs. CoRR abs/1806.08829 (2018) - [i4]Luana Ruiz, Fernando Gama, Antonio G. Marques, Alejandro Ribeiro:
Median activation functions for graph neural networks. CoRR abs/1810.12165 (2018) - 2017
- [c6]Fernando Gama, Alejandro Ribeiro
Distributed estimation of smooth graph power spectral density. GlobalSIP 2017: 643-647 - [c5]Fernando Gama, Helder M. Arruda
Improving Our Understanding of the Behavior of Bees Through Anomaly Detection Techniques. ICANN (2) 2017: 520-527 - [c4]Fernando Gama, Alejandro Ribeiro
Weak law of large numbers for stationary graph processes. ICASSP 2017: 4124-4128 - [i3]Fernando Gama, Geert Leus, Antonio Garcia Marques, Alejandro Ribeiro:
Convolutional Neural Networks Via Node-Varying Graph Filters. CoRR abs/1710.10355 (2017) - 2016
- [c3]Fernando Gama, Antonio G. Marques
Rethinking sketching as sampling: Linear transforms of graph signals. ACSSC 2016: 522-526 - [c2]Fernando Gama, Santiago Segarra
Overlapping clustering of network data using cut metrics. ICASSP 2016: 6415-6419 - [c1]Wallace P. Lira, Fernando Gama, Hivana Melo Barbosa Dall'Agnol
VCloud: adding interactiveness to word clouds for knowledge exploration in large unstructured texts. SAC 2016: 193-198 - [i2]Fernando Gama, Antonio G. Marques
Rethinking Sketching as Sampling: A Graph Signal Processing Approach. CoRR abs/1611.00119 (2016) - [i1]Fernando Gama, Santiago Segarra, Alejandro Ribeiro:
Hierarchical Overlapping Clustering of Network Data Using Cut Metrics. CoRR abs/1611.01393 (2016) - 2015
- [j2]Fernando Gama, Daniel Casaglia, Bruno Cernuschi-Frías
Analysis and Comparison of Biased Affine Estimators. IEEE Trans. Signal Process. 63(4): 859-869 (2015) - 2014
- [j1]Bruno Cernuschi-Frías
Deepest Minimum Criterion for Biased Affine Estimation. IEEE Trans. Signal Process. 62(9): 2437-2449 (2014)
Coauthor Index
[c39] [j21] [j19] [j17] [j16] [j15] [j14] [i40] [i39] [j12] [c32] [c31] [c30] [c29] [c28] [c27] [i34] [i33] [j11] [j10] [j9] [j8] [j7] [c25] [c24] [c23] [c22] [c21] [i29] [i28] [i27] [i26] [i25] [i24] [i23] [i22] [i21] [i20] [i18] [j6] [j5] [j4] [c20] [c19] [c18] [c17] [c16] [c15] [c14] [c13] [c12] [i17] [i16] [i15] [i14] [i13] [i12] [i11] [i10] [i9] [i8] [j3] [c11] [c10] [c9] [c8] [c7] [i7] [i6] [i5] [i4] [c6] [c4] [i3] [c3] [c2] [i2] [i1]
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last updated on 2024-12-02 21:30 CET by the dblp team
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