
Joint inference of multiple graphs with hidden variables from stationary graph signals
Learning graphs from sets of nodal observations represents a prominent p...
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A Robust Alternative for Graph Convolutional Neural Networks via Graph Neighborhood Filters
Graph convolutional neural networks (GCNNs) are popular deep learning ar...
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Untrained Graph Neural Networks for Denoising
A fundamental problem in signal processing is to denoise a signal. While...
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Lowrank Stateaction Valuefunction Approximation
Value functions are central to Dynamic Programming and Reinforcement Lea...
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Joint Inference of Multiple Graphs from Matrix Polynomials
Inferring graph structure from observations on the nodes is an important...
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Tensor Graph Convolutional Networks for Multirelational and Robust Learning
The era of "data deluge" has sparked renewed interest in graphbased lea...
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An Underparametrized Deep Decoder Architecture for Graph Signals
While deep convolutional architectures have achieved remarkable results ...
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InvariancePreserving Localized Activation Functions for Graph Neural Networks
Graph signals are signals with an irregular structure that can be descri...
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Distributed Network Caching via Dynamic Programming
Nextgeneration communication networks are envisioned to extensively uti...
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A Recurrent Graph Neural Network for MultiRelational Data
The era of data deluge has sparked the interest in graphbased learning ...
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Median activation functions for graph neural networks
Graph neural networks (GNNs) have been shown to replicate convolutional ...
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Convolutional Neural Networks Architectures for Signals Supported on Graphs
We describe two architectures that generalize convolutional neural netwo...
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MIMO Graph Filters for Convolutional Neural Networks
Superior performance and ease of implementation have fostered the adopti...
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Antonio G. Marques
verfied profile
Professor of Electrical and Computer Engineering. Working on optimization, signal processing and machine learning. Author of more than 100 journal and conference papers (several of them awarded). Recipient of the 2020 EURASIP Early Career Award. Current research interests include graph signal processing, machine learning over graphs, and geometric deep learning.