research
∙
09/16/2023
Recovering Missing Node Features with Local Structure-based Embeddings
Node features bolster graph-based learning when exploited jointly with n...
share
research
∙
09/14/2023
SC-MAD: Mixtures of Higher-order Networks for Data Augmentation
The myriad complex systems with multiway interactions motivate the exten...
research
∙
09/13/2023
Data Augmentation via Subgroup Mixup for Improving Fairness
In this work, we propose data augmentation via pairwise mixup across sub...
research
∙
08/11/2023
Enhancing Network Management Using Code Generated by Large Language Models
Analyzing network topologies and communication graphs plays a crucial ro...
research
∙
06/11/2023
Deep Demixing: Reconstructing the Evolution of Network Epidemics
We propose the deep demixing (DDmix) model, a graph autoencoder that can...
research
∙
05/08/2023
Solving Linear Inverse Problems using Higher-Order Annealed Langevin Diffusion
We propose a solution for linear inverse problems based on higher-order ...
research
∙
04/30/2023
Hypergraphs with Edge-Dependent Vertex Weights: Spectral Clustering based on the 1-Laplacian
We propose a flexible framework for defining the 1-Laplacian of a hyperg...
research
∙
04/18/2023
Learning to Transmit with Provable Guarantees in Wireless Federated Learning
We propose a novel data-driven approach to allocate transmit power for f...
research
∙
04/02/2023
Deep Graph Unfolding for Beamforming in MU-MIMO Interference Networks
We develop an efficient and near-optimal solution for beamforming in mul...
research
∙
03/02/2023
A Deep Reinforcement Learning-Based Resource Scheduler for Massive MIMO Networks
The large number of antennas in massive MIMO systems allows the base sta...
research
∙
02/11/2023
Windowed Fourier Analysis for Signal Processing on Graph Bundles
We consider the task of representing signals supported on graph bundles,...
research
∙
02/02/2023
Unsupervised Learning of Sampling Distributions for Particle Filters
Accurate estimation of the states of a nonlinear dynamical system is cru...
research
∙
12/04/2022
Joint graph learning from Gaussian observations in the presence of hidden nodes
Graph learning problems are typically approached by focusing on learning...
research
∙
11/19/2022
Delay-aware Backpressure Routing Using Graph Neural Networks
We propose a throughput-optimal biased backpressure (BP) algorithm for r...
research
∙
11/16/2022
Graph Filters for Signal Processing and Machine Learning on Graphs
Filters are fundamental in extracting information from data. For time se...
research
∙
11/05/2022
Neural multi-event forecasting on spatio-temporal point processes using probabilistically enriched transformers
Predicting discrete events in time and space has many scientific applica...
research
∙
10/27/2022
GraphMAD: Graph Mixup for Data Augmentation using Data-Driven Convex Clustering
We develop a novel data-driven nonlinear mixup mechanism for graph data ...
research
∙
09/17/2022
Joint Network Topology Inference via a Shared Graphon Model
We consider the problem of estimating the topology of multiple networks ...
research
∙
08/15/2022
Hypergraphs with Edge-Dependent Vertex Weights: p-Laplacians and Spectral Clustering
We study p-Laplacians and spectral clustering for a recently proposed hy...
research
∙
03/27/2022
Distributed Link Sparsification for Scalable Scheduling Using Graph Neural Networks
Distributed scheduling algorithms for throughput or utility maximization...
research
∙
02/11/2022
Graphon-aided Joint Estimation of Multiple Graphs
We consider the problem of estimating the topology of multiple networks ...
research
∙
01/27/2022
Graph-based Algorithm Unfolding for Energy-aware Power Allocation in Wireless Networks
We develop a novel graph-based trainable framework to maximize the weigh...
research
∙
01/16/2022
Hypergraph Cuts with Edge-Dependent Vertex Weights
We develop a framework for incorporating edge-dependent vertex weights (...
research
∙
11/15/2021
Power Allocation for Wireless Federated Learning using Graph Neural Networks
We propose a data-driven approach for power allocation in the context of...
research
∙
10/14/2021
Stability Analysis of Unfolded WMMSE for Power Allocation
Power allocation is one of the fundamental problems in wireless networks...
research
∙
10/13/2021
Robust MIMO Detection using Hypernetworks with Learned Regularizers
Optimal symbol detection in multiple-input multiple-output (MIMO) system...
research
∙
10/07/2021
Label Propagation across Graphs: Node Classification using Graph Neural Tangent Kernels
Graph neural networks (GNNs) have achieved superior performance on node ...
research
∙
10/06/2021
Unrolling Particles: Unsupervised Learning of Sampling Distributions
Particle filtering is used to compute good nonlinear estimates of comple...
research
∙
10/05/2021
Joint inference of multiple graphs with hidden variables from stationary graph signals
Learning graphs from sets of nodal observations represents a prominent p...
research
∙
10/02/2021
A Robust Alternative for Graph Convolutional Neural Networks via Graph Neighborhood Filters
Graph convolutional neural networks (GCNNs) are popular deep learning ar...
research
∙
09/24/2021
Untrained Graph Neural Networks for Denoising
A fundamental problem in signal processing is to denoise a signal. While...
research
∙
09/14/2021
ML-aided power allocation for Tactical MIMO
We study the problem of optimal power allocation in single-hop multi-ant...
research
∙
09/12/2021
Link Scheduling using Graph Neural Networks
Efficient scheduling of transmissions is a key problem in wireless netwo...
research
∙
08/16/2021
Robust Hierarchical Clustering for Directed Networks: An Axiomatic Approach
We provide a complete taxonomic characterization of robust hierarchical ...
research
∙
06/14/2021
Signal processing on simplicial complexes
Higher-order networks have so far been considered primarily in the conte...
research
∙
05/27/2021
An Impossibility Theorem for Node Embedding
With the increasing popularity of graph-based methods for dimensionality...
research
∙
05/19/2021
Free Energy Node Embedding via Generalized Skip-gram with Negative Sampling
A widely established set of unsupervised node embedding methods can be i...
research
∙
04/07/2021
Graph Reordering for Cache-Efficient Near Neighbor Search
Graph search is one of the most successful algorithmic trends in near ne...
research
∙
02/20/2021
GIST: Distributed Training for Large-Scale Graph Convolutional Networks
The graph convolutional network (GCN) is a go-to solution for machine le...
research
∙
02/19/2021
Co-clustering Vertices and Hyperedges via Spectral Hypergraph Partitioning
We propose a novel method to co-cluster the vertices and hyperedges of h...
research
∙
02/19/2021
Principled Simplicial Neural Networks for Trajectory Prediction
We consider the construction of neural network architectures for data on...
research
∙
01/14/2021
Signal Processing on Higher-Order Networks: Livin' on the Edge ... and Beyond
This tutorial paper presents a didactic treatment of the emerging topic ...
research
∙
12/17/2020
Rank-One Measurements of Low-Rank PSD Matrices Have Small Feasible Sets
We study the role of the constraint set in determining the solution to l...
research
∙
11/18/2020
Distributed Scheduling using Graph Neural Networks
A fundamental problem in the design of wireless networks is to efficient...
research
∙
11/18/2020
Adaptive Contention Window Design using Deep Q-learning
We study the problem of adaptive contention window (CW) design for rando...
research
∙
10/21/2020
Network topology change-point detection from graph signals with prior spectral signatures
We consider the problem of sequential graph topology change-point detect...
research
∙
10/16/2020
Joint Inference of Multiple Graphs from Matrix Polynomials
Inferring graph structure from observations on the nodes is an important...
research
∙
08/02/2019
An Underparametrized Deep Decoder Architecture for Graph Signals
While deep convolutional architectures have achieved remarkable results ...
research
∙
05/22/2019
Blind identification of stochastic block models from dynamical observations
We consider a blind identification problem in which we aim to recover a ...
research
∙
05/17/2019
