Elvin Isufi

IEEE Trans. Pattern Anal. Mach. Intell., December, 2023

Learning Stochastic Graph Neural Networks With Constrained Variance.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2023

Online Edge Flow Imputation on Networks.

[BibT_eX]

[DOI]

Rohan T. Money

Joshin Krishnan

IEEE Signal Process. Lett., 2023

Learning graphs and simplicial complexes from data.

[BibT_eX]

[DOI]

CoRR, 2023

On the Trade-Off between Stability and Representational Capacity in Graph Neural Networks.

[BibT_eX]

[DOI]

Amanda Prorok

CoRR, 2023

Uncertainty in Graph Contrastive Learning with Bayesian Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2023

Hodge-Compositional Edge Gaussian Processes.

[BibT_eX]

[DOI]

Viacheslav Borovitskiy

CoRR, 2023

Hodge-Aware Contrastive Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Convolutional Learning on Simplicial Complexes.

[BibT_eX]

[DOI]

CoRR, 2023

Deep Statistical Solver for Distribution System State Estimation.

[BibT_eX]

[DOI]

CoRR, 2023

Online Edge Flow Prediction Over Expanding Simplicial Complexes.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2023

Simplicial Vector Autoregressive Model For Streaming Edge Flows.

[BibT_eX]

[DOI]

Joshin Krishnan

Rohan T. Money

Proceedings of the IEEE International Conference on Acoustics, 2023

Online Vector Autoregressive Models Over Expanding Graphs.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2023

Graph-Time Trend Filtering and Unrolling Network.

[BibT_eX]

[DOI]

Mohammad Sabbaqi

Proceedings of the 31st European Signal Processing Conference, 2023

2022

Simplicial Convolutional Filters.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2022

Quantization Analysis and Robust Design for Distributed Graph Filters.

[BibT_eX]

[DOI]

Leila Ben Saad

IEEE Trans. Signal Process., 2022

Task-Aware Connectivity Learning for Incoming Nodes Over Growing Graphs.

[BibT_eX]

[DOI]

Alan Hanjalic

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

EdgeNets: Edge Varying Graph Neural Networks.

[BibT_eX]

[DOI]

Fernando Gama

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

Graph Filters for Signal Processing and Machine Learning on Graphs.

[BibT_eX]

[DOI]

CoRR, 2022

Graph filtering over expanding graphs.

[BibT_eX]

[DOI]

CoRR, 2022

Graph-Time Convolutional Autoencoders.

[BibT_eX]

[DOI]

Proceedings of the Learning on Graphs Conference, 2022

Simplicial Convolutional Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2022

Convolutional Filtering in Simplicial Complexes.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2022

Learning Expanding Graphs for Signal Interpolation.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2022

Dynamic Bi-Colored Graph Partitioning.

[BibT_eX]

[DOI]

Proceedings of the 30th European Signal Processing Conference, 2022

Simplicial Trend Filtering (Invited Paper).

[BibT_eX]

[DOI]

Proceedings of the 56th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2022, Pacific Grove, CA, USA, October 31, 2022

Learning Stable Graph Neural Networks via Spectral Regularization.

[BibT_eX]

[DOI]

Proceedings of the 56th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2022, Pacific Grove, CA, USA, October 31, 2022

Online Filtering over Expanding Graphs.

[BibT_eX]

[DOI]

Proceedings of the 56th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2022, Pacific Grove, CA, USA, October 31, 2022

2021

Stochastic Graph Neural Networks.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2021

Stability of graph convolutional neural networks to stochastic perturbations.

[BibT_eX]

[DOI]

Signal Process., 2021

Accuracy-diversity trade-off in recommender systems via graph convolutions.

[BibT_eX]

[DOI]

Matteo Pocchiari

Alan Hanjalic

Inf. Process. Manag., 2021

Learning Time-Varying Graphs from Online Data.

[BibT_eX]

[DOI]

CoRR, 2021

Graph-Time Convolutional Neural Networks.

[BibT_eX]

[DOI]

Gabriele Mazzola

CoRR, 2021

GReS: Workshop on Graph Neural Networks for Recommendation and Search.

[BibT_eX]

[DOI]

Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021

Nonlinear State-Space Generalizations of Graph Convolutional Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2021

Online Time-Varying Topology Identification Via Prediction-Correction Algorithms.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2021

Topological Volterra Filters.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2021

Variance-Constrained Learning for Stochastic Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2021

Sampling Graph Signals with Sparse Dictionary Representation.

[BibT_eX]

[DOI]

Kaiwen Zhang

Mario Coutino

Proceedings of the 29th European Signal Processing Conference, 2021

Finite Impulse Response Filters for Simplicial Complexes.

[BibT_eX]

[DOI]

Proceedings of the 29th European Signal Processing Conference, 2021

Online Graph Learning From Time-Varying Structural Equation Models.

[BibT_eX]

[DOI]

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

2020

State-Space Network Topology Identification From Partial Observations.

[BibT_eX]

[DOI]

IEEE Trans. Signal Inf. Process. over Networks, 2020

Graphs, Convolutions, and Neural Networks: From Graph Filters to Graph Neural Networks.

[BibT_eX]

[DOI]

IEEE Signal Process. Mag., 2020

Observing and tracking bandlimited graph processes from sampled measurements.

[BibT_eX]

[DOI]

Signal Process., 2020

Graphs, Convolutions, and Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2020

Graph-time spectral analysis for atrial fibrillation.

[BibT_eX]

[DOI]

Miao Sun

Natasja M. S. de Groot

Richard C. Hendriks

Biomed. Signal Process. Control., 2020

Graph-Adaptive Activation Functions for Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 30th IEEE International Workshop on Machine Learning for Signal Processing, 2020

Forecasting Multi-Dimensional Processes Over Graphs.

[BibT_eX]

[DOI]

Alberto Natali

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Active Semi-Supervised Learning for Diffusions on Graphs.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Node Varying Regularization for Graph Signals.

[BibT_eX]

[DOI]

Proceedings of the 28th European Signal Processing Conference, 2020

Towards Finite-Time Consensus with Graph Convolutional Neural Networks.

[BibT_eX]

[DOI]

Bianca Iancu

Proceedings of the 28th European Signal Processing Conference, 2020

State-Space Based Network Topology Identification.

[BibT_eX]

[DOI]

Proceedings of the 28th European Signal Processing Conference, 2020

Rational Chebyshev Graph Filters.

[BibT_eX]

[DOI]

Oxana Rimleanscaia

Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

2019

Forecasting Time Series With VARMA Recursions on Graphs.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2019

Controllability of Bandlimited Graph Processes Over Random Time Varying Graphs.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2019

Advances in Distributed Graph Filtering.

[BibT_eX]

[DOI]

Mario Coutino

IEEE Trans. Signal Process., 2019

Filter Design for Autoregressive Moving Average Graph Filters.

[BibT_eX]

[DOI]

Jiani Liu

IEEE Trans. Signal Inf. Process. over Networks, 2019

On the Transferability of Spectral Graph Filters.

[BibT_eX]

[DOI]

Ron Levie

Gitta Kutyniok

CoRR, 2019

Graph Filtering with Quantization over Random Time-varying Graphs.

[BibT_eX]

[DOI]

Leila Ben Saad

Proceedings of the 2019 IEEE Global Conference on Signal and Information Processing, 2019

A Graph Signal Processing Framework for Atrial Activity Extraction.

[BibT_eX]

[DOI]

Miao Sun

Natasja M. S. de Groot

Richard C. Hendriks

Proceedings of the 27th European Signal Processing Conference, 2019

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

[BibT_eX]

[DOI]

Fernando Gama

Proceedings of the 27th European Signal Processing Conference, 2019

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

[BibT_eX]

[DOI]

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

2018

Adaptive Graph Signal Processing: Algorithms and Optimal Sampling Strategies.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2018

Blind Graph Topology Change Detection.

[BibT_eX]

[DOI]

Ashvant S. U. Mahabir

IEEE Signal Process. Lett., 2018

Distributed Wiener-Based Reconstruction of Graph Signals.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Statistical Signal Processing Workshop, 2018

Control of Graph Signals Over Random Time-Varying Graphs.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Observing Bandlimited Graph Processes from Subsampled Measurements.

[BibT_eX]

[DOI]

Proceedings of the 52nd Asilomar Conference on Signals, Systems, and Computers, 2018

On The Limits of Finite-Time Distributed Consensus Through Successive Local Linear Operations.

[BibT_eX]

[DOI]

Proceedings of the 52nd Asilomar Conference on Signals, Systems, and Computers, 2018

2017

Filtering Random Graph Processes Over Random Time-Varying Graphs.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2017

Autoregressive Moving Average Graph Filtering.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2017

Autoregressive moving average graph filters a stable distributed implementation.

[BibT_eX]

[DOI]

Andreas Loukas

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Distributed sparsified graph filters for denoising and diffusion tasks.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Autoregressive moving average graph filter design.

[BibT_eX]

[DOI]

Jiani Liu

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

Distributed recursive least squares strategies for adaptive reconstruction of graph signals.

[BibT_eX]

[DOI]

Proceedings of the 25th European Signal Processing Conference, 2017

Distributed edge-variant graph filters.

[BibT_eX]

[DOI]

Mario Coutino

Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017

Predicting the evolution of stationary graph signals.

[BibT_eX]

[DOI]

Andreas Loukas

Nathanaël Perraudin

Proceedings of the 51st Asilomar Conference on Signals, Systems, and Computers, 2017

2016

Advanced flooding-based routing protocols for underwater sensor networks.

[BibT_eX]

[DOI]

Henry Dol

EURASIP J. Adv. Signal Process., 2016

Distributed Time-Varying Graph Filtering.

[BibT_eX]

[DOI]

CoRR, 2016

2-Dimensional finite impulse response graph-temporal filters.

[BibT_eX]

[DOI]

Paolo Banelli

Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

Separable autoregressive moving average graph-temporal filters.

[BibT_eX]

[DOI]

Proceedings of the 24th European Signal Processing Conference, 2016

2015

Stochastic graph filtering on time-varying graphs.

[BibT_eX]

[DOI]

Proceedings of the 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2015

2014

Network Coding for Flooding-Based Routing in Underwater Sensor Networks.

[BibT_eX]

[DOI]