| Autoregressive moving average graph filtering E Isufi, A Loukas, A Simonetto, G Leus IEEE Transactions on Signal Processing 65 (2), 274-288, 2016 | 291 | 2016 |
| Deep learning methods for flood mapping: a review of existing applications and future research directions R Bentivoglio, E Isufi, SN Jonkman, R Taormina Hydrology and Earth System Sciences Discussions 2022, 1-50, 2022 | 211 | 2022 |
| Graphs, convolutions, and neural networks: From graph filters to graph neural networks F Gama, E Isufi, G Leus, A Ribeiro IEEE Signal Processing Magazine 37 (6), 128-138, 2020 | 198 | 2020 |
| Forecasting time series with VARMA recursions on graphs E Isufi, A Loukas, N Perraudin, G Leus IEEE Transactions on Signal Processing 67 (18), 4870-4885, 2019 | 125 | 2019 |
| Advances in distributed graph filtering M Coutino, E Isufi, G Leus IEEE Transactions on Signal Processing 67 (9), 2320-2333, 2019 | 113 | 2019 |
| Adaptive graph signal processing: Algorithms and optimal sampling strategies P Di Lorenzo, P Banelli, E Isufi, S Barbarossa, G Leus IEEE Transactions on Signal Processing 66 (13), 3584-3598, 2018 | 110 | 2018 |
| Filtering random graph processes over random time-varying graphs E Isufi, A Loukas, A Simonetto, G Leus IEEE Transactions on Signal Processing 65 (16), 4406-4421, 2017 | 103 | 2017 |
| Edgenets: Edge varying graph neural networks E Isufi, F Gama, A Ribeiro IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (11), 7457 …, 2021 | 87 | 2021 |
| Accuracy-diversity trade-off in recommender systems via graph convolutions E Isufi, M Pocchiari, A Hanjalic Information Processing & Management 58 (2), 102459, 2021 | 80 | 2021 |
| Filter design for autoregressive moving average graph filters J Liu, E Isufi, G Leus IEEE Transactions on Signal and Information Processing over Networks 5 (1 …, 2018 | 74 | 2018 |
| Graph filters for signal processing and machine learning on graphs E Isufi, F Gama, DI Shuman, S Segarra IEEE Transactions on Signal Processing, 2024 | 67 | 2024 |
| On the transferability of spectral graph filters R Levie, E Isufi, G Kutyniok 2019 13th International conference on Sampling Theory and Applications …, 2019 | 62 | 2019 |
| Simplicial convolutional neural networks M Yang, E Isufi, G Leus ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 56 | 2022 |
| Finite impulse response filters for simplicial complexes M Yang, E Isufi, MT Schaub, G Leus 2021 29th European Signal Processing Conference (EUSIPCO), 2005-2009, 2021 | 45 | 2021 |
| State-space network topology identification from partial observations M Coutino, E Isufi, T Maehara, G Leus IEEE Transactions on Signal and Information Processing over Networks 6, 211-225, 2020 | 43 | 2020 |
| Simplicial convolutional filters M Yang, E Isufi, MT Schaub, G Leus IEEE Transactions on Signal Processing 70, 4633-4648, 2022 | 38 | 2022 |
| Learning time-varying graphs from online data A Natali, E Isufi, M Coutino, G Leus IEEE Open Journal of Signal Processing 3, 212-228, 2022 | 37 | 2022 |
| Observing and tracking bandlimited graph processes from sampled measurements E Isufi, P Banelli, P Di Lorenzo, G Leus Signal Processing 177, 107749, 2020 | 37* | 2020 |
| Separable autoregressive moving average graph-temporal filters E Isufi, A Loukas, A Simonetto, G Leus 2016 24th European Signal Processing Conference (EUSIPCO), 200-204, 2016 | 33 | 2016 |
| 2-dimensional finite impulse response graph-temporal filters E Isufi, G Leus, P Banelli 2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2016 | 31 | 2016 |
Geert LeusFull Professor at Delft University of Technology (TU Delft)Bestätigte E-Mail-Adresse bei tudelft.nl
