Hierarchical clustering methods and algorithms for asymmetric networks. - Gunnar E. Carlsson; Facundo Mémoli; Alejandro Ribeiro; Santiago Segarra (ACSSC, 2013)

Hierarchical clustering and consensus in trust networks. - Santiago Segarra; Alejandro Ribeiro (CAMSAP, 2013)

Alternative axiomatic constructions for hierarchical clustering of asymmetric networks. - Gunnar E. Carlsson; Facundo Mémoli; Alejandro Ribeiro; Santiago Segarra (GlobalSIP, 2013)

Axiomatic construction of hierarchical clustering in asymmetric networks. - Gunnar E. Carlsson; Facundo Mémoli; Alejandro Ribeiro; Santiago Segarra (ICASSP, 2013)

Authorship attribution using function words adjacency networks. - Santiago Segarra; Mark Eisen; Alejandro Ribeiro (ICASSP, 2013)

Dithering and betweenness centrality in weighted graphs. - Santiago Segarra; Alejandro Ribeiro (GlobalSIP, 2014)

A stable betweenness centrality measure in networks. - Santiago Segarra; Alejandro Ribeiro (ICASSP, 2014)

Hierarchical Quasi-Clustering Methods for Asymmetric Networks. - Gunnar E. Carlsson; Facundo Mémoli; Alejandro Ribeiro; Santiago Segarra (ICML, 2014)

Diffusion distance for signals supported on networks. - Weiyu Huang; Santiago Segarra; Alejandro Ribeiro (ACSSC, 2015)

Sampling of graph signals: Successive local aggregations at a single node. - Santiago Segarra; Antonio G. Marques; Geert Leus; Alejandro Ribeiro (ACSSC, 2015)

Distributed implementation of linear network operators using graph filters. - Santiago Segarra; Antonio G. Marques; Alejandro Ribeiro (Allerton, 2015)

Aggregation sampling of graph signals in the presence of noise. - Santiago Segarra; Antonio G. Marques; Geert Leus; Alejandro Ribeiro (CAMSAP, 2015)

Blind identification of graph filters with sparse inputs. - Santiago Segarra; Gonzalo Mateos; Antonio G. Marques; Alejandro Ribeiro (CAMSAP, 2015)

Interpolation of graph signals using shift-invariant graph filters. - Santiago Segarra; Antonio G. Marques; Geert Leus; Alejandro Ribeiro (EUSIPCO, 2015)

Reconstruction of graph signals: Percolation from a single seeding node. - Santiago Segarra; Antonio G. Marques; Geert Leus; Alejandro Ribeiro (GlobalSIP, 2015)

Stability and continuity of centrality measures in weighted graphs. - Santiago Segarra; Alejandro Ribeiro (ICASSP, 2015)

Distributed Linear Network Operators using Graph Filters. - Santiago Segarra; Antonio G. Marques; Alejandro Ribeiro (CoRR, 2015)

Diffusion and Superposition Distances for Signals Supported on Networks. - Santiago Segarra; Weiyu Huang; Alejandro Ribeiro (IEEE Trans. Signal Inf. Process. over Networks, 2015)

Authorship Attribution Through Function Word Adjacency Networks. - Santiago Segarra; Mark Eisen; Alejandro Ribeiro (IEEE Trans. Signal Process., 2015)

Network topology identification from imperfect spectral templates. - Santiago Segarra; Antonio G. Marques; Gonzalo Mateos; Alejandro Ribeiro (ACSSC, 2016)

Center-weighted median graph filters. - Santiago Segarra; Antonio G. Marques; Gonzalo R. Arce; Alejandro Ribeiro (GlobalSIP, 2016)

Overlapping clustering of network data using cut metrics. - Fernando Gama; Santiago Segarra; Alejandro Ribeiro (ICASSP, 2016)

Diffusion filtering of graph signals and its use in recommendation systems. - Jeremy Ma; Weiyu Huang; Santiago Segarra; Alejandro Ribeiro (ICASSP, 2016)

Space-shift sampling of graph signals. - Santiago Segarra; Antonio G. Marques; Geert Leus; Alejandro Ribeiro (ICASSP, 2016)

Blind identification of graph filters with multiple sparse inputs. - Santiago Segarra; Antonio G. Marques; Gonzalo Mateos; Alejandro Ribeiro (ICASSP, 2016)

Linear network operators using node-variant graph filters. - Santiago Segarra; Antonio G. Marques; Alejandro Ribeiro (ICASSP, 2016)

Stationary graph processes: Nonparametric spectral estimation. - Santiago Segarra; Antonio G. Marques; Geert Leus; Alejandro Ribeiro (SAM, 2016)

Network topology identification from spectral templates. - Santiago Segarra; Antonio G. Marques; Gonzalo Mateos; Alejandro Ribeiro (SSP, 2016)

Excisive Hierarchical Clustering Methods for Network Data. - Gunnar E. Carlsson; Facundo Mémoli; Alejandro Ribeiro; Santiago Segarra (CoRR, 2016)

Sampling of Graph Signals With Successive Local Aggregations. - Antonio G. Marques; Santiago Segarra; Geert Leus; Alejandro Ribeiro (IEEE Trans. Signal Process., 2016)

Reconstruction of Graph Signals Through Percolation from Seeding Nodes. - Santiago Segarra; Antonio G. Marques; Geert Leus; Alejandro Ribeiro (IEEE Trans. Signal Process., 2016)

Joint inference of networks from stationary graph signals. - Santiago Segarra; Yuhao Wang 005; Caroline Uhler; Antonio G. Marques (ACSSC, 2017)

Design of weighted median graph filters. - Santiago Segarra; Antonio G. Marques; Gonzalo R. Arce; Alejandro Ribeiro (CAMSAP, 2017)

Network inference from consensus dynamics. - Santiago Segarra; Michael T. Schaub; Ali Jadbabaie (CDC, 2017)

Graph-signal reconstruction and blind deconvolution for diffused sparse inputs. - David Ramírez 001; Antonio G. Marques; Santiago Segarra (ICASSP, 2017)

Stationary graph processes: Parametric power spectral estimation. - Santiago Segarra; Antonio G. Marques; Geert Leus; Alejandro Ribeiro (ICASSP, 2017)

Robust network topology inference. - Santiago Segarra; Antonio G. Marques; Gonzalo Mateos; Alejandro Ribeiro (ICASSP, 2017)

Network topology inference from non-stationary graph signals. - Rasoul Shafipour; Santiago Segarra; Antonio G. Marques; Gonzalo Mateos (ICASSP, 2017)

Centrality measures for graphons. - Marco Avella-Medina; Francesca Parise; Michael T. Schaub; Santiago Segarra (CoRR, 2017)

The Dual Graph Shift Operator: Identifying the Support of the Frequency Domain. - Geert Leus; Santiago Segarra; Alejandro Ribeiro; Antonio G. Marques (CoRR, 2017)

Admissible Hierarchical Clustering Methods and Algorithms for Asymmetric Networks. - Gunnar E. Carlsson; Facundo Mémoli; Alejandro Ribeiro; Santiago Segarra (IEEE Trans. Signal Inf. Process. over Networks, 2017)

Network Topology Inference from Spectral Templates. - Santiago Segarra; Antonio G. Marques; Gonzalo Mateos; Alejandro Ribeiro (IEEE Trans. Signal Inf. Process. over Networks, 2017)

Stationary Graph Processes and Spectral Estimation. - Antonio G. Marques; Santiago Segarra; Geert Leus; Alejandro Ribeiro (IEEE Trans. Signal Process., 2017)

Blind Identification of Graph Filters. - Santiago Segarra; Gonzalo Mateos; Antonio G. Marques; Alejandro Ribeiro (IEEE Trans. Signal Process., 2017)

Optimal Graph-Filter Design and Applications to Distributed Linear Network Operators. - Santiago Segarra; Antonio G. Marques; Alejandro Ribeiro (IEEE Trans. Signal Process., 2017)

Directed Network Topology Inference via Graph Filter Identification. - Rasoul Shafipour; Santiago Segarra; Antonio G. Marques; Gonzalo Mateos (DSW, 2018)

Flow Smoothing and Denoising: Graph Signal Processing in the Edge-Space. - Michael T. Schaub; Santiago Segarra (GlobalSIP, 2018)

Enhancing Geometric Deep Learning via Graph Filter Deconvolution. - Jingkang Yang; Santiago Segarra (GlobalSIP, 2018)

Demixing and Blind Deconvolution of Graph-Diffused Sparse Signals. - Fernando Jose Iglesias Garcia; Santiago Segarra; Samuel Rey-Escudero; Antonio G. Marques; David Ramírez 001 (ICASSP, 2018)

Identifying Undirected Network Structure via Semidefinite Relaxation. - Rasoul Shafipour; Santiago Segarra; Antonio G. Marques; Gonzalo Mateos (ICASSP, 2018)

Community Detection from Low-Rank Excitations of a Graph Filter. - Hoi-To Wai; Santiago Segarra; Asuman E. Ozdaglar; Anna Scaglione; Ali Jadbabaie (ICASSP, 2018)

Network Topology Inference From Input-Output Diffusion Pairs. - Santiago Segarra; Antonio G. Marques; Mohak Goyal; Samuel Rey-Escudero (SSP, 2018)

Hierarchical clustering of asymmetric networks. - Gunnar E. Carlsson; Facundo Mémoli; Alejandro Ribeiro; Santiago Segarra (Adv. Data Anal. Classif., 2018)

Identifying the Topology of Undirected Networks from Diffused Non-stationary Graph Signals. - Rasoul Shafipour; Santiago Segarra; Antonio G. Marques; Gonzalo Mateos (CoRR, 2018)

Stylometric analysis of Early Modern period English plays. - Mark Eisen; Alejandro Ribeiro; Santiago Segarra; Gabriel Egan (Digit. Scholarsh. Humanit., 2018)

Hierarchical Overlapping Clustering of Network Data Using Cut Metrics. - Fernando Gama; Santiago Segarra; Alejandro Ribeiro (IEEE Trans. Signal Inf. Process. over Networks, 2018)

HodgeNet: Graph Neural Networks for Edge Data. - T. Mitchell Roddenberry; Santiago Segarra (ACSSC, 2019)

An Underparametrized Deep Decoder Architecture for Graph Signals. - Samuel Rey; Antonio G. Marques; Santiago Segarra (CAMSAP, 2019)

Spectral Partitioning of Time-varying Networks with Unobserved Edges. - Michael T. Schaub; Santiago Segarra; Hoi-To Wai (ICASSP, 2019)

Estimation of Network Processes via Blind Graph Multi-filter Identification. - Yu Zhu 003; Fernando Jose Iglesias Garcia; Antonio G. Marques; Santiago Segarra (ICASSP, 2019)

Neural Network Architectures for Electricity Consumption Forecasting. - Cristina Heghedus; Santiago Segarra; Antorweep Chakravorty; Chunming Rong (iThings/GreenCom/CPSCom/SmartData, 2019)

Graph-based Semi-Supervised & Active Learning for Edge Flows. - Junteng Jia; Michael T. Schaub; Santiago Segarra; Austin R. Benson (KDD, 2019)

Connecting the Dots: Identifying Network Structure via Graph Signal Processing. - Gonzalo Mateos; Santiago Segarra; Antonio G. Marques; Alejandro Ribeiro (IEEE Signal Process. Mag., 2019)

Blind Estimation of Eigenvector Centrality from Graph Signals: Beyond Low-pass Filtering. - T. Mitchell Roddenberry; Santiago Segarra (ACSSC, 2020)

Generative Adversarial Networks for Graph Data Imputation from Signed Observations. - Amarlingam Madapu; Santiago Segarra; Sundeep Prabhakar Chepuri; Antonio G. Marques (ICASSP, 2020)

Blind Inference of Centrality Rankings from Graph Signals. - T. Mitchell Roddenberry; Santiago Segarra (ICASSP, 2020)

Metric Representations of Networks: A Uniqueness Result. - Santiago Segarra; T. Mitchell Roddenberry; Facundo Mémoli; Alejandro Ribeiro (ICASSP, 2020)

Rank-One Measurements of Low-Rank PSD Matrices Have Small Feasible Sets. - T. Mitchell Roddenberry; Santiago Segarra; Anastasios Kyrillidis (CoRR, 2020)

Automated detection of activity onset after postictal generalized EEG suppression. - Bishal Lamichhane; Yejin Kim 001; Santiago Segarra; Guoqiang Zhang 001; Samden D. Lhatoo; Jaison Hampson; Xiaoqian Jiang (BMC Medical Informatics Decis. Mak., 2020)

Blind Identification of Stochastic Block Models from Dynamical Observations. - Michael T. Schaub; Santiago Segarra; John N. Tsitsiklis (SIAM J. Math. Data Sci., 2020)

Signal Processing on Directed Graphs: The Role of Edge Directionality When Processing and Learning From Network Data. - Antonio G. Marques; Santiago Segarra; Gonzalo Mateos (IEEE Signal Process. Mag., 2020)

Centrality Measures for Graphons: Accounting for Uncertainty in Networks. - Marco Avella-Medina; Francesca Parise; Michael T. Schaub; Santiago Segarra (IEEE Trans. Netw. Sci. Eng., 2020)

Network Inference From Consensus Dynamics With Unknown Parameters. - Yu Zhu 003; Michael T. Schaub; Ali Jadbabaie; Santiago Segarra (IEEE Trans. Signal Inf. Process. over Networks, 2020)

Exact Blind Community Detection From Signals on Multiple Graphs. - T. Mitchell Roddenberry; Michael T. Schaub; Hoi-To Wai; Santiago Segarra (IEEE Trans. Signal Process., 2020)

Blind Community Detection From Low-Rank Excitations of a Graph Filter. - Hoi-To Wai; Santiago Segarra; Asuman E. Ozdaglar; Anna Scaglione; Ali Jadbabaie (IEEE Trans. Signal Process., 2020)

Estimating Network Processes via Blind Identification of Multiple Graph Filters. - Yu Zhu 003; Fernando Jose Iglesias Garcia; Antonio G. Marques; Santiago Segarra (IEEE Trans. Signal Process., 2020)

Node Embedding based on the Free Energy Distance. - Yu Zhu 003; Ananthram Swami; Santiago Segarra (ACSCC, 2021)

Energy-Efficient Power Allocation in Wireless Networks using Graph Neural Networks. - Boning Li; Gunjan Verma; Chirag Rao; Santiago Segarra (ACSCC, 2021)

A Robust Alternative for Graph Convolutional Neural Networks via Graph Neighborhood Filters. - Victor M. Tenorio; Samuel Rey; Fernando Gama; Santiago Segarra; Antonio G. Marques (ACSCC, 2021)

Co-clustering Vertices and Hyperedges via Spectral Hypergraph Partitioning. - Yu Zhu 003; Boning Li; Santiago Segarra (EUSIPCO, 2021)

Deep Demixing: Reconstructing the Evolution of Epidemics using Graph Neural Networks. - Gojko Cutura; Boning Li; Ananthram Swami; Santiago Segarra (EUSIPCO, 2021)

Efficient Power Allocation Using Graph Neural Networks and Deep Algorithm Unfolding. - Arindam Chowdhury; Gunjan Verma; Chirag Rao; Ananthram Swami; Santiago Segarra (ICASSP, 2021)

Network Topology Change-Point Detection from Graph Signals with Prior Spectral Signatures. - Chiraag Kaushik; T. Mitchell Roddenberry; Santiago Segarra (ICASSP, 2021)

Adaptive Contention Window Design Using Deep Q-Learning. - Abhishek Kumar; Gunjan Verma; Chirag Rao; Ananthram Swami; Santiago Segarra (ICASSP, 2021)

Network Topology Inference with Graphon Spectral Penalties. - T. Mitchell Roddenberry; Madeline Navarro; Santiago Segarra (ICASSP, 2021)

Distributed Scheduling Using Graph Neural Networks. - Zhongyuan Zhao 002; Gunjan Verma; Chirag Rao; Ananthram Swami; Santiago Segarra (ICASSP, 2021)

Principled Simplicial Neural Networks for Trajectory Prediction. - T. Mitchell Roddenberry; Nicholas Glaze; Santiago Segarra (ICML, 2021)

ML-aided power allocation for Tactical MIMO. - Arindam Chowdhury; Gunjan Verma; Chirag Rao; Ananthram Swami; Santiago Segarra (MILCOM, 2021)

GIST: Distributed Training for Large-Scale Graph Convolutional Networks. - Cameron R. Wolfe; Jingkang Yang; Arindam Chowdhury; Chen Dun; Artun Bayer; Santiago Segarra; Anastasios Kyrillidis (CoRR, 2021)

Signal processing on simplicial complexes. - Michael T. Schaub; Jean-Baptiste Seby; Florian Frantzen; T. Mitchell Roddenberry; Yu Zhu 003; Santiago Segarra (CoRR, 2021)

Robust Hierarchical Clustering for Directed Networks: An Axiomatic Approach. - Gunnar E. Carlsson; Facundo Mémoli; Santiago Segarra (SIAM J. Appl. Algebra Geom., 2021)

Graph-signal Reconstruction and Blind Deconvolution for Structured Inputs. - David Ramírez 001; Antonio G. Marques; Santiago Segarra (Signal Process., 2021)

Signal processing on higher-order networks: Livin' on the edge... and beyond. - Michael T. Schaub; Yu Zhu 003; Jean-Baptiste Seby; T. Mitchell Roddenberry; Santiago Segarra (Signal Process., 2021)

Blind Inference of Eigenvector Centrality Rankings. - T. Mitchell Roddenberry; Santiago Segarra (IEEE Trans. Signal Process., 2021)

Unfolding WMMSE Using Graph Neural Networks for Efficient Power Allocation. - Arindam Chowdhury; Gunjan Verma; Chirag Rao; Ananthram Swami; Santiago Segarra (IEEE Trans. Wirel. Commun., 2021)

Conversational Turn-taking as a Stochastic Process on Networks. - Lisa O'Bryan; Santiago Segarra; Jensine Paoletti; Stephanie Zajac; Margaret E. Beier; Ashutosh Sabharwal; Matthew A. Wettergreen; Eduardo Salas (IEEECONF, 2022)

Joint graph learning from Gaussian observations in the presence of hidden nodes. - Samuel Rey; Madeline Navarro; Andrei Buciulea; Santiago Segarra; Antonio G. Marques (IEEECONF, 2022)

Hypergraph 1-Spectral Clustering with General Submodular Weights. - Yu Zhu 003; Boning Li; Santiago Segarra (IEEECONF, 2022)

Robust MIMO Detection using Hypernetworks with Learned Regularizers. - Nicolas Zilberstein; Chris Dick; Rahman Doost-Mohammady; Ashutosh Sabharwal; Santiago Segarra (EUSIPCO, 2022)

Detection by Sampling: Massive MIMO Detector based on Langevin Dynamics. - Nicolas Zilberstein; Chris Dick; Rahman Doost-Mohammady; Ashutosh Sabharwal; Santiago Segarra (EUSIPCO, 2022)

Minding the gap between fast heuristics and their optimal counterparts. - Pooria Namyar; Behnaz Arzani; Ryan Beckett; Santiago Segarra; Himanshu Raj; Srikanth Kandula (HotNets, 2022)

Label Propagation Across Graphs: Node Classification Using Graph Neural Tangent Kernels. - Artun Bayer; Arindam Chowdhury; Santiago Segarra (ICASSP, 2022)

Stability Analysis of Unfolded WMMSE for Power Allocation. - Arindam Chowdhury; Fernando Gama; Santiago Segarra (ICASSP, 2022)

Unrolling Particles: Unsupervised Learning of Sampling Distributions. - Fernando Gama; Nicolas Zilberstein; Richard G. Baraniuk; Santiago Segarra (ICASSP, 2022)

Power Allocation for Wireless Federated Learning Using Graph Neural Networks. - Boning Li; Ananthram Swami; Santiago Segarra (ICASSP, 2022)

Graphon-Aided Joint Estimation of Multiple Graphs. - Madeline Navarro; Santiago Segarra (ICASSP, 2022)

Joint Inference of Multiple Graphs with Hidden Variables from Stationary Graph Signals. - Samuel Rey; Andrei Buciulea; Madeline Navarro; Santiago Segarra; Antonio G. Marques (ICASSP, 2022)

Hodgelets: Localized Spectral Representations of Flows On Simplicial Complexes. - T. Mitchell Roddenberry; Florian Frantzen; Michael T. Schaub; Santiago Segarra (ICASSP, 2022)

Distributed Link Sparsification for Scalable Scheduling Using Graph Neural Networks. - Zhongyuan Zhao 002; Ananthram Swami; Santiago Segarra (ICASSP, 2022)

Delay-Oriented Distributed Scheduling Using Graph Neural Networks. - Zhongyuan Zhao 002; Gunjan Verma; Ananthram Swami; Santiago Segarra (ICASSP, 2022)

Hypergraphs with Edge-Dependent Vertex Weights: Spectral Clustering Based on the 1-Laplacian. - Yu Zhu 003; Boning Li; Santiago Segarra (ICASSP, 2022)

Graph Reordering for Cache-Efficient Near Neighbor Search. - Benjamin Coleman; Santiago Segarra; Alexander J. Smola; Anshumali Shrivastava (NeurIPS, 2022)

Hypergraph cuts with edge-dependent vertex weights. - Yu Zhu 003; Santiago Segarra (Appl. Netw. Sci., 2022)

Neural multi-event forecasting on spatio-temporal point processes using probabilistically enriched transformers. - Negar Erfanian; Santiago Segarra; Maarten V. de Hoop (CoRR, 2022)

Joint Inference of Multiple Graphs from Matrix Polynomials. - Madeline Navarro; Yuhao Wang 005; Antonio G. Marques; Caroline Uhler; Santiago Segarra (J. Mach. Learn. Res., 2022)

How the Word Adjacency Network (WAN) works. - Paul Brown; Mark Eisen; Santiago Segarra; Alejandro Ribeiro; Gabriel Egan (Digit. Scholarsh. Humanit., 2022)

Joint Network Topology Inference Via a Shared Graphon Model. - Madeline Navarro; Santiago Segarra (IEEE Trans. Signal Process., 2022)

Untrained Graph Neural Networks for Denoising. - Samuel Rey; Santiago Segarra; Reinhard Heckel; Antonio G. Marques (IEEE Trans. Signal Process., 2022)

On Local Distributions in Graph Signal Processing. - T. Mitchell Roddenberry; Fernando Gama; Richard G. Baraniuk; Santiago Segarra (IEEE Trans. Signal Process., 2022)

ML-Based Feedback-Free Adaptive MCS Selection for Massive Multi-User MIMO. - Qing An; Mehdi Zafari; Chris Dick; Santiago Segarra; Ashutosh Sabharwal; Rahman Doost-Mohammady (ACSSC, 2023)

Learning Non-myopic Power Allocation in Constrained Scenarios. - Arindam Chowdhury; Santiago Paternain; Gunjan Verma; Ananthram Swami; Santiago Segarra (ACSSC, 2023)

State and Dynamics Estimation with the Kalman-Langevin filter. - Martin Sevilla; Nicolas Zilberstein; Benjamin Cox; Sara Pérez-Vieites; Víctor Elvira; Santiago Segarra (ACSSC, 2023)

Enhanced Backpressure Routing Using Wireless Link Features. - Zhongyuan Zhao 002; Gunjan Verma; Ananthram Swami; Santiago Segarra (CAMSAP, 2023)

Securing Public Clouds using Dynamic Communication Graphs. - Sathiya Kumaran Mani; Kevin Hsieh; Santiago Segarra; Trevor Eberl; Ranveer Chandra; Eliran Azulai; Narayan Annamalai; Deepak Bansal; Srikanth Kandula (HotNets, 2023)

Enhancing Network Management Using Code Generated by Large Language Models. - Sathiya Kumaran Mani; Yajie Zhou; Kevin Hsieh; Santiago Segarra; Trevor Eberl; Eliran Azulai; Ido Frizler; Ranveer Chandra; Srikanth Kandula (HotNets, 2023)

Graph Representation Learning For Stroke Recurrence Prediction. - Nicholas Glaze; Artun Bayer; Xiaoqian Jiang; Sean I. Savitz; Santiago Segarra (ICASSP, 2023)

Graphmad: Graph Mixup for Data Augmentation Using Data-Driven Convex Clustering. - Madeline Navarro; Santiago Segarra (ICASSP, 2023)

Signal Processing On Product Spaces. - T. Mitchell Roddenberry; Vincent P. Grande; Florian Frantzen; Michael T. Schaub; Santiago Segarra (ICASSP, 2023)

Windowed Fourier Analysis for Signal Processing on Graph Bundles. - T. Mitchell Roddenberry; Santiago Segarra (ICASSP, 2023)

Delay-Aware Backpressure Routing Using Graph Neural Networks. - Zhongyuan Zhao 002; Bojan Radojicic; Gunjan Verma; Ananthram Swami; Santiago Segarra (ICASSP, 2023)

Accelerated Massive MIMO Detector Based on Annealed Underdamped Langevin Dynamics. - Nicolas Zilberstein; Chris Dick; Rahman Doost-Mohammady; Ashutosh Sabharwal; Santiago Segarra (ICASSP, 2023)

Graph-based Deterministic Policy Gradient for Repetitive Combinatorial Optimization Problems. - Zhongyuan Zhao 002; Ananthram Swami; Santiago Segarra (ICLR, 2023)

Learnable Digital Twin for Efficient Wireless Network Evaluation. - Boning Li; Timofey Efimov; Abhishek Kumar; Jose Cortes; Gunjan Verma; Ananthram Swami; Santiago Segarra (MILCOM, 2023)

A Deep Reinforcement Learning-Based Resource Scheduler for Massive MIMO Networks. - Qing An; Santiago Segarra; Chris Dick; Ashutosh Sabharwal; Rahman Doost-Mohammady (CoRR, 2023)

Deep Demixing: Reconstructing the Evolution of Network Epidemics. - Boning Li; Gojko Cutura; Ananthram Swami; Santiago Segarra (CoRR, 2023)

Enhancing Network Management Using Code Generated by Large Language Models. - Sathiya Kumaran Mani; Yajie Zhou; Kevin Hsieh; Santiago Segarra; Ranveer Chandra; Srikanth Kandula (CoRR, 2023)

Limits of Dense Simplicial Complexes. - T. Mitchell Roddenberry; Santiago Segarra (J. Mach. Learn. Res., 2023)

Unsupervised Learning of Sampling Distributions for Particle Filters. - Fernando Gama; Nicolas Zilberstein; Martin Sevilla; Richard G. Baraniuk; Santiago Segarra (IEEE Trans. Signal Process., 2023)

Enhanced Graph-Learning Schemes Driven by Similar Distributions of Motifs. - Samuel Rey; T. Mitchell Roddenberry; Santiago Segarra; Antonio G. Marques (IEEE Trans. Signal Process., 2023)

Graph-Based Algorithm Unfolding for Energy-Aware Power Allocation in Wireless Networks. - Boning Li; Gunjan Verma; Santiago Segarra (IEEE Trans. Wirel. Commun., 2023)

Hypergraphs with edge-dependent vertex weights: p-Laplacians and spectral clustering. - Yu Zhu 003; Santiago Segarra (Frontiers Big Data, 2023)

Link Scheduling Using Graph Neural Networks. - Zhongyuan Zhao 002; Gunjan Verma; Chirag Rao; Ananthram Swami; Santiago Segarra (IEEE Trans. Wirel. Commun., 2023)

Annealed Langevin Dynamics for Massive MIMO Detection. - Nicolas Zilberstein; Chris Dick; Rahman Doost-Mohammady; Ashutosh Sabharwal; Santiago Segarra (IEEE Trans. Wirel. Commun., 2023)

Free Energy Node Embedding via Generalized Skip-Gram With Negative Sampling. - Yu Zhu 003; Ananthram Swami; Santiago Segarra (IEEE Trans. Knowl. Data Eng., 2023)

Joint embedding of biological networks for cross-species functional alignment. - Lechuan Li; Ruth Dannenfelser; Yu Zhu 003; Nathaniel Hejduk; Santiago Segarra; Vicky Yao (Bioinform., 2023)

"I would I had that corporal soundness": Pervez Rizvi's Analysis of the Word Adjacency Network Method of Authorship Attribution. - Gabriel Egan; Mark Eisen; Alejandro Ribeiro; Santiago Segarra (Digit. Scholarsh. Humanit., 2023)

Multiuser Fair Resource Allocation for Block-stationary Wireless Channels. - Reza Ramezanpour; Santiago Segarra; Ashutosh Sabharwal (IEEECONF, 2024)

Structure-Guided Input Graph for GNNs Facing Heterophily. - Victor M. Tenorio; Madeline Navarro; Samuel Rey; Santiago Segarra; Antonio G. Marques (IEEECONF, 2024)

An Impossibility Theorem for Node Embedding. - T. Mitchell Roddenberry; Yu Zhu 003; Santiago Segarra (AISTATS, 2024)

Estimation of partially known Gaussian graphical models with score-based structural priors. - Martin Sevilla; Antonio G. Marques; Santiago Segarra (AISTATS, 2024)

Efficient Path Planning with Soft Homology Constraints. - Carlos A. Taveras; Santiago Segarra; César A. Uribe (CCTA, 2024)

Mitigating Subpopulation Bias for Fair Network Topology Inference. - Madeline Navarro; Samuel Rey; Andrei Buciulea; Antonio G. Marques; Santiago Segarra (EUSIPCO, 2024)

Towards Safer Heuristics With XPlain. - Pantea Karimi; Solal Pirelli; Siva Kesava Reddy Kakarla; Ryan Beckett; Santiago Segarra; Beibin Li; Pooria Namyar; Behnaz Arzani (HotNets, 2024)

End-to-End Performance Analysis of Learning-enabled Systems. - Pooria Namyar; Michael Schapira; Ramesh Govindan; Santiago Segarra; Ryan Beckett; Siva Kesava Reddy Kakarla; Behnaz Arzani (HotNets, 2024)

Congestion-Aware Distributed Task Offloading in Wireless Multi-Hop Networks Using Graph Neural Networks. - Zhongyuan Zhao 002; Jake B. Perazzone; Gunjan Verma; Santiago Segarra (ICASSP, 2024)

End-to-End Learning of Gaussian Mixture Proposals Using Differentiable Particle Filters and Neural Networks. - Benjamin Cox; Sara Pérez-Vieites; Nicolas Zilberstein; Martin Sevilla; Santiago Segarra; Víctor Elvira (ICASSP, 2024)

Data Augmentation via Subgroup Mixup for Improving Fairness. - Madeline Navarro; Camille Olivia Little; Genevera I. Allen; Santiago Segarra (ICASSP, 2024)

SC-MAD: Mixtures of Higher-Order Networks for Data Augmentation. - Madeline Navarro; Santiago Segarra (ICASSP, 2024)

Bayesian Topology Inference on Partially Known Networks from Input-Output Pairs. - Martin Sevilla; Santiago Segarra (ICASSP, 2024)

Recovering Missing Node Features with Local Structure-Based Embeddings. - Victor M. Tenorio; Madeline Navarro; Santiago Segarra; Antonio G. Marques (ICASSP, 2024)

Joint Channel Estimation and Data Detection in Massive Mimo Systems Based on Diffusion Models. - Nicolas Zilberstein; Ananthram Swami; Santiago Segarra (ICASSP, 2024)

Ant Backpressure Routing for Wireless Multi-hop Networks with Mixed Traffic Patterns. - Negar Erfaniantaghvayi; Zhongyuan Zhao 002; Kevin S. Chan; Gunjan Verma; Ananthram Swami; Santiago Segarra (MILCOM, 2024)

Fair GLASSO: Estimating Fair Graphical Models with Unbiased Statistical Behavior. - Madeline Navarro; Samuel Rey; Andrei Buciulea; Antonio G. Marques; Santiago Segarra (NeurIPS, 2024)

NetVigil: Robust and Low-Cost Anomaly Detection for East-West Data Center Security. - Kevin Hsieh; Mike Wong 003; Santiago Segarra; Sathiya Kumaran Mani; Trevor Eberl; Anatoliy Panasyuk; Ravi Netravali; Ranveer Chandra; Srikanth Kandula (NSDI, 2024)

Finding Adversarial Inputs for Heuristics using Multi-level Optimization. - Pooria Namyar; Behnaz Arzani; Ryan Beckett; Santiago Segarra; Himanshu Raj; Umesh Krishnaswamy; Ramesh Govindan; Srikanth Kandula (NSDI, 2024)

Solving Max-Min Fair Resource Allocations Quickly on Large Graphs. - Pooria Namyar; Behnaz Arzani; Srikanth Kandula; Santiago Segarra; Daniel Crankshaw; Umesh Krishnaswamy; Ramesh Govindan; Himanshu Raj (NSDI, 2024)

GraSSRep: Graph-Based Self-supervised Learning for Repeat Detection in Metagenomic Assembly. - Ali Azizpour; Advait Balaji; Todd J. Treangen; Santiago Segarra (RECOMB, 2024)

Reference-free structural variant detection in microbiomes via long-read co-assembly graphs. - Kristen D. Curry; Feiqiao Brian Yu; Summer E. Vance; Santiago Segarra; Devaki Bhaya; Rayan Chikhi; Eduardo P. C. Rocha; Todd J. Treangen (Bioinform., 2024)

Repulsive Score Distillation for Diverse Sampling of Diffusion Models. - Nicolas Zilberstein; Morteza Mardani; Santiago Segarra (CoRR, 2024)

Biased Backpressure Routing Using Link Features and Graph Neural Networks. - Zhongyuan Zhao 002; Bojan Radojicic; Gunjan Verma; Ananthram Swami; Santiago Segarra (CoRR, 2024)

GLANCE: Graph-based Learnable Digital Twin for Communication Networks. - Boning Li; Gunjan Verma; Timofey Efimov; Abhishek Kumar; Santiago Segarra (CoRR, 2024)

ML-SPEAK: A Theory-Guided Machine Learning Method for Studying and Predicting Conversational Turn-taking Patterns. - Lisa O'Bryan; Madeline Navarro; Juan Segundo Hevia; Santiago Segarra (CoRR, 2024)

Fully Distributed Online Training of Graph Neural Networks in Networked Systems. - Rostyslav Olshevskyi; Zhongyuan Zhao 002; Kevin S. Chan; Gunjan Verma; Ananthram Swami; Santiago Segarra (CoRR, 2024)

Objective Communication Patterns Associated With Team Member Effectiveness in Real-World Virtual Teams. - Lisa O'Bryan; Tim Oxendahl; Xu Chen 011; Daniel McDuff; Santiago Segarra; Matthew A. Wettergreen; Margaret E. Beier; Ashutosh Sabharwal (Hum. Factors, 2024)

A reply to Pervez Rizvi's letter. - Gabriel Egan; Mark Eisen; Alejandro Ribeiro; Santiago Segarra (Digit. Scholarsh. Humanit., 2024)

Graph Filters for Signal Processing and Machine Learning on Graphs. - Elvin Isufi; Fernando Gama; David I Shuman; Santiago Segarra (IEEE Trans. Signal Process., 2024)

Joint Network Topology Inference in the Presence of Hidden Nodes. - Madeline Navarro; Samuel Rey; Andrei Buciulea; Antonio G. Marques; Santiago Segarra (IEEE Trans. Signal Process., 2024)

Solving Linear Inverse Problems Using Higher-Order Annealed Langevin Diffusion. - Nicolas Zilberstein; Ashutosh Sabharwal; Santiago Segarra (IEEE Trans. Signal Process., 2024)

Deep Graph Unfolding for Beamforming in MU-MIMO Interference Networks. - Arindam Chowdhury; Gunjan Verma; Ananthram Swami; Santiago Segarra (IEEE Trans. Wirel. Commun., 2024)

Learning to Transmit With Provable Guarantees in Wireless Federated Learning. - Boning Li; Jake B. Perazzone; Ananthram Swami; Santiago Segarra (IEEE Trans. Wirel. Commun., 2024)

Data science for graphs. - Gunnar E. Carlsson; Santiago Segarra (J. Appl. Comput. Topol., 2024)

GIST: distributed training for large-scale graph convolutional networks. - Cameron R. Wolfe; Jingkang Yang; Fangshuo Liao; Arindam Chowdhury; Chen Dun; Artun Bayer; Santiago Segarra; Anastasios Kyrillidis (J. Appl. Comput. Topol., 2024)

Scalable Implicit Graphon Learning. - Ali Azizpour; Nicolas Zilberstein; Santiago Segarra (AISTATS, 2025)

Joint Task Offloading and Routing in Wireless Multi-hop Networks Using Biased Backpressure Algorithm. - Zhongyuan Zhao 002; Jake B. Perazzone; Gunjan Verma; Kevin S. Chan; Ananthram Swami; Santiago Segarra (ICASSP, 2025)

Online Network Inference from Graph-Stationary Signals with Hidden Nodes. - Andrei Buciulea; Madeline Navarro; Samuel Rey; Santiago Segarra; Antonio G. Marques (ICASSP, 2025)

Fair CoVariance Neural Networks. - Andrea Cavallo; Madeline Navarro; Santiago Segarra; Elvin Isufi (ICASSP, 2025)

Bayesian Filtering on Graphs. - Bishwadeep Das; Madeline Navarro; Santiago Segarra; Elvin Isufi (ICASSP, 2025)

Low-Rank Tensors for Multi-Dimensional Markov Models. - Madeline Navarro; Sergio Rozada; Antonio G. Marques; Santiago Segarra (ICASSP, 2025)

Redesigning graph filter-based GNNs to relax the homophily assumption. - Samuel Rey; Madeline Navarro; Victor M. Tenorio; Santiago Segarra; Antonio G. Marques (ICASSP, 2025)

Repulsive Latent Score Distillation for Solving Inverse Problems. - Nicolas Zilberstein; Morteza Mardani; Santiago Segarra (ICLR, 2025)

Securing Public Cloud Networks with Efficient Role-based Micro-Segmentation. - Sathiya Kumaran Mani; Kevin Hsieh; Santiago Segarra; Ranveer Chandra; Yajie Zhou; Srikanth Kandula (NSDI, 2025)

Learning state and proposal dynamics in state-space models using differentiable particle filters and neural networks. - Benjamin Cox; Santiago Segarra; Víctor Elvira (Signal Process., 2025)

Generalizing Biased Backpressure Routing and Scheduling to Wireless Multi-hop Networks with Advanced Air-interfaces. - Zhongyuan Zhao 002; Yujun Ming; Ananthram Swami; Kevin S. Chan; Fikadu Dagefu; Santiago Segarra (CoRR, 2025)

SeLR: Sparsity-enhanced Lagrangian Relaxation for Computation Offloading at the Edge. - Negar Erfaniantaghvayi; Zhongyuan Zhao 002; Kevin S. Chan; Ananthram Swami; Santiago Segarra (CoRR, 2025)

Graph Guided Diffusion: Unified Guidance for Conditional Graph Generation. - Victor M. Tenorio; Nicolas Zilberstein; Santiago Segarra; Antonio G. Marques (CoRR, 2025)

A Few Moments Please: Scalable Graphon Learning via Moment Matching. - Reza Ramezanpour; Victor M. Tenorio; Antonio G. Marques; Ashutosh Sabharwal; Santiago Segarra (CoRR, 2025)

Model-Driven Graph Contrastive Learning. - Ali Azizpour; Nicolas Zilberstein; Santiago Segarra (CoRR, 2025)

Infinity Search: Approximate Vector Search with Projections on q-Metric Spaces. - Antonio Pariente; Ignacio Hounie; Santiago Segarra; Alejandro Ribeiro (CoRR, 2025)

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery. - Victor M. Tenorio; Madeline Navarro; Samuel Rey; Santiago Segarra; Antonio G. Marques (CoRR, 2025)

Distributed Link Sparsification for Scalable Scheduling Using Graph Neural Networks (Journal Version). - Zhongyuan Zhao 002; Gunjan Verma; Ananthram Swami; Santiago Segarra (CoRR, 2025)

Adaptive Graph Coarsening for Efficient GNN Training. - Rostyslav Olshevskyi; Madeline Navarro; Santiago Segarra (CoRR, 2025)

Adaptive Node Feature Selection For Graph Neural Networks. - Ali Azizpour; Madeline Navarro; Santiago Segarra (CoRR, 2025)

From Moments to Models: Graphon Mixture-Aware Mixup and Contrastive Learning. - Ali Azizpour; Reza Ramezanpour; Ashutosh Sabharwal; Santiago Segarra (CoRR, 2025)

Estimating Fair Graphs from Graph-Stationary Data. - Madeline Navarro; Andrei Buciulea; Samuel Rey; Antonio G. Marques; Santiago Segarra (CoRR, 2025)

Learning Time-Varying Turn-Taking Behavior in Group Conversations. - Madeline Navarro; Lisa O'Bryan; Santiago Segarra (CoRR, 2025)