Max-min feasible point pursuit for non-convex QCQP. - Charilaos I. Kanatsoulis; Nicholas D. Sidiropoulos (ACSSC, 2015)

Large-Scale Regularized Sumcor GCCA via Penalty-Dual Decomposition. - Charilaos I. Kanatsoulis; Xiao Fu 001; Nicholas D. Sidiropoulos; Mingyi Hong 001 (ICASSP, 2018)

Hyperspectral Super-Resolution Via Coupled Tensor Factorization: Identifiability and Algorithms. - Charilaos I. Kanatsoulis; Xiao Fu 001; Nicholas D. Sidiropoulos; Wing-Kin Ma (ICASSP, 2018)

Hyperspectral Super-Resolution: Combining Low Rank Tensor and Matrix Structure. - Charilaos I. Kanatsoulis; Xiao Fu 001; Nicholas D. Sidiropoulos; Wing-Kin Ma (ICIP, 2018)

Hyperspectral Super-Resolution: A Coupled Tensor Factorization Approach. - Charilaos I. Kanatsoulis; Xiao Fu 001; Nicholas D. Sidiropoulos; Wing-Kin Ma (IEEE Trans. Signal Process., 2018)

Large-scale Canonical Polyadic Decomposition via Regular Tensor Sampling. - Charilaos I. Kanatsoulis; Nicholas D. Sidiropoulos (EUSIPCO, 2019)

Regular Sampling of Tensor Signals: Theory and Application to FMRI. - Charilaos I. Kanatsoulis; Nicholas D. Sidiropoulos; Mehmet Akçakaya; Xiao Fu 001 (ICASSP, 2019)

Structured SUMCOR Multiview Canonical Correlation Analysis for Large-Scale Data. - Charilaos I. Kanatsoulis; Xiao Fu 001; Nicholas D. Sidiropoulos; Mingyi Hong 001 (IEEE Trans. Signal Process., 2019)

Downlink Channel Feedback for FDD Massive MIMO Systems via Tensor Compression and Sampling. - Mohamed Salah Ibrahim; Charilaos I. Kanatsoulis; Nicholas D. Sidiropoulos (ACSSC, 2020)

Tendi: Tensor Disaggregation from Multiple Coarse Views. - Faisal M. Almutairi; Charilaos I. Kanatsoulis; Nicholas D. Sidiropoulos (PAKDD (2), 2020)

Tensor Completion From Regular Sub-Nyquist Samples. - Charilaos I. Kanatsoulis; Xiao Fu 001; Nicholas D. Sidiropoulos; Mehmet Akçakaya (IEEE Trans. Signal Process., 2020)

TeX-Graph: Coupled tensor-matrix knowledge-graph embedding for COVID-19 drug repurposing. - Charilaos I. Kanatsoulis; Nicholas D. Sidiropoulos (SDM, 2021)

Prema: Principled Tensor Data Recovery From Multiple Aggregated Views. - Faisal M. Almutairi; Charilaos I. Kanatsoulis; Nicholas D. Sidiropoulos (IEEE J. Sel. Top. Signal Process., 2021)

Generalized Canonical Correlation Analysis: A Subspace Intersection Approach. - Mikael Sørensen; Charilaos I. Kanatsoulis; Nicholas D. Sidiropoulos (IEEE Trans. Signal Process., 2021)

Space-Time Graph Neural Networks. - Samar Hadou; Charilaos I. Kanatsoulis; Alejandro Ribeiro (ICLR, 2022)

GAGE: Geometry Preserving Attributed Graph Embeddings. - Charilaos I. Kanatsoulis; Nicholas D. Sidiropoulos (WSDM, 2022)

Deep Convolutional Neural Networks for Multi-Target Tracking: A Transfer Learning Approach. - Damian Owerko; Charilaos I. Kanatsoulis; Alejandro Ribeiro; Donald J. Bucci Jr.; Jennifer Bondarchuk (CoRR, 2022)

Solving Large-Scale Spatial Problems with Convolutional Neural Networks. - Damian Owerko; Charilaos I. Kanatsoulis; Alejandro Ribeiro (ACSSC, 2023)

Multi-Target Tracking with Transferable Convolutional Neural Networks. - Damian Owerko; Charilaos I. Kanatsoulis; Jennifer Bondarchuk; Donald J. Bucci; Alejandro Ribeiro (CAMSAP, 2023)

Space-Time Graph Neural Networks with Stochastic Graph Perturbations. - Samar Hadou; Charilaos I. Kanatsoulis; Alejandro Ribeiro (ICASSP, 2023)

Transferability of Convolutional Neural Networks in Stationary Learning Tasks. - Damian Owerko; Charilaos I. Kanatsoulis; Jennifer Bondarchuk; Donald J. Bucci Jr.; Alejandro Ribeiro (CoRR, 2023)

Network Alignment with Transferable Graph Autoencoders. - Jiashu He; Charilaos I. Kanatsoulis; Alejandro Ribeiro (CoRR, 2023)

Online Canonical Correlation Analysis via Rayleigh-Ritz Projections. - Vassilis Kalantzis; Panagiotis A. Traganitis; Charilaos I. Kanatsoulis (IEEECONF, 2024)

Graph Neural Networks are More Powerful than We Think. - Charilaos I. Kanatsoulis; Alejandro Ribeiro (ICASSP, 2024)

Counting Graph Substructures with Graph Neural Networks. - Charilaos I. Kanatsoulis; Alejandro Ribeiro (ICLR, 2024)

A Graph Autoencoder Approach to Crowdsourcing. - Panagiotis A. Traganitis; Charilaos I. Kanatsoulis (SAM, 2024)

T-Gae: Transferable Graph Autoencoder for Network Alignment. - Jiashu He; Charilaos I. Kanatsoulis; Alejandro Ribeiro (LoG, 2024)

Generalizability of Graph Neural Networks for Decentralized Unlabeled Motion Planning. - Shreyas Muthusamy; Damian Owerko; Charilaos I. Kanatsoulis; Saurav Agarwal; Alejandro Ribeiro (CoRR, 2024)

LoRTA: Low Rank Tensor Adaptation of Large Language Models. - Ignacio Hounie; Charilaos I. Kanatsoulis; Arnuv Tandon; Alejandro Ribeiro (CoRR, 2024)

Learning Efficient Positional Encodings with Graph Neural Networks. - Charilaos I. Kanatsoulis; Evelyn Choi; Stefanie Jegelka; Jure Leskovec; Alejandro Ribeiro (ICLR, 2025)

Learning Efficient Positional Encodings with Graph Neural Networks. - Charilaos I. Kanatsoulis; Evelyn Choi; Stephanie Jegelka; Jure Leskovec; Alejandro Ribeiro (CoRR, 2025)

RelGNN: Composite Message Passing for Relational Deep Learning. - Tianlang Chen; Charilaos I. Kanatsoulis; Jure Leskovec (CoRR, 2025)

KGGen: Extracting Knowledge Graphs from Plain Text with Language Models. - Belinda Mo; Kyssen Yu; Joshua Kazdan; Proud Mpala; Lisa Yu; Chris Cundy; Charilaos I. Kanatsoulis; Sanmi Koyejo (CoRR, 2025)

Relational Graph Transformer. - Vijay Prakash Dwivedi; Sri Jaladi; Yangyi Shen; Federico López; Charilaos I. Kanatsoulis; Rishi Puri; Matthias Fey; Jure Leskovec (CoRR, 2025)

Relational Deep Learning: Challenges, Foundations and Next-Generation Architectures. - Vijay Prakash Dwivedi; Charilaos I. Kanatsoulis; Shenyang Huang; Jure Leskovec (CoRR, 2025)