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

Bulat Kerimov, Roberto Bentivoglio, Alexander Garzón, Elvin Isufi, Franz Tscheikner-Gratl, David Bernhard Steffelbauer, Riccardo Taormina (2023), Assessing the performances and transferability of graph neural network metamodels for water distribution systems, In Journal of Hydroinformatics Volume 25 p.2223-2234.

Benjamin Habib, Elvin Isufi, Ward van Breda, Arjen Jongepier, Jochen L. Cremer (2023), Deep Statistical Solver for Distribution System State Estimation, In IEEE Transactions on Power Systems Volume 39 p.4039-4050.

Mohammad Sabbaqi, Elvin Isufi (2023), Graph-Time Convolutional Neural Networks: Architecture and Theoretical Analysis, In IEEE Transactions on Pattern Analysis and Machine Intelligence Volume 45 p.14625-14638.

Mohammad Sabbaqi, Elvin Isufi (2023), Graph-Time Trend Filtering and Unrolling Network, In Proceedings of the 2023 31st European Signal Processing Conference (EUSIPCO) p.1230-1234, IEEE .

Zhan Gao, Elvin Isufi (2023), Learning Stochastic Graph Neural Networks With Constrained Variance, In IEEE Transactions on Signal Processing Volume 71 p.358-371.

Maosheng Yang, Bishwadeep Das, Elvin Isufi (2023), Online Edge Flow Prediction Over Expanding Simplicial Complexes, In Proceedings of the ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE .

Bishwadeep Das, Elvin Isufi (2023), Online Vector Autoregressive Models Over Expanding Graphs, In Proceedings of the ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE .

Roberto Bentivoglio, Elvin Isufi, Sebastiaan Nicolas Jonkman, Riccardo Taormina (2023), Rapid spatio-temporal flood modelling via hydraulics-based graph neural networks, In Hydrology and Earth System Sciences Volume 27 p.4227–4246.

Rohan Money, Joshin Krishnan, Baltasar Beferull-Lozano, Elvin Isufi (2023), Scalable and Privacy-Aware Online Learning of Nonlinear Structural Equation Models, In IEEE Open Journal of Signal Processing Volume 4 p.61-70.