9 citations · 21 across the 14 of their papers we have counts for
14 papers
Deep Demixing: Reconstructing the Evolution of Network Epidemics
Boning Li, Gojko Čutura, Ananthram Swami +1
We propose the deep demixing (DDmix) model, a graph autoencoder that can reconstruct epidemics evolving over networks from partial or aggregated temporal information. Assuming know…
Learnable Digital Twin for Efficient Wireless Network Evaluation
Boning Li, Timofey Efimov, Abhishek Kumar +4
Network digital twins (NDTs) facilitate the estimation of key performance indicators (KPIs) before physically implementing a network, thereby enabling efficient optimization of the…
Hypergraphs with Edge-Dependent Vertex Weights: Spectral Clustering based on the 1-Laplacian
Yu Zhu, Boning Li, Santiago Segarra
We propose a flexible framework for defining the 1-Laplacian of a hypergraph that incorporates edge-dependent vertex weights. These weights are able to reflect varying importance o…
Deep Graph Unfolding for Beamforming in MU-MIMO Interference Networks
Arindam Chowdhury, Gunjan Verma, Ananthram Swami +1
We develop an efficient and near-optimal solution for beamforming in multi-user multiple-input-multiple-output single-hop wireless ad-hoc interference networks. Inspired by the wei…
Windowed Fourier Analysis for Signal Processing on Graph Bundles
T. Mitchell Roddenberry, Santiago Segarra
We consider the task of representing signals supported on graph bundles, which are generalizations of product graphs that allow for "twists" in the product structure. Leveraging th…
Unsupervised Learning of Sampling Distributions for Particle Filters
Fernando Gama, Nicolas Zilberstein, Martin Sevilla +2
Accurate estimation of the states of a nonlinear dynamical system is crucial for their design, synthesis, and analysis. Particle filters are estimators constructed by simulating tr…