| Understanding the basis of graph signal processing via an intuitive example-driven approach [lecture notes] L Stankovic, DP Mandic, M Dakovic, I Kisil, E Sejdic, AG Constantinides IEEE Signal Processing Magazine 36 (6), 133-145, 2019 | 88 | 2019 |
| Demystifying the coherence index in compressive sensing [lecture notes] L Stankovic, DP Mandic, M Dakovic, I Kisil IEEE Signal Processing Magazine 37 (1), 152-162, 2020 | 26 | 2020 |
| Common and individual feature extraction using tensor decompositions: A remedy for the curse of dimensionality? I Kisil, GG Calvi, A Cichocki, DP Mandic 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 15* | 2018 |
| HOTTBOX: Higher order tensor ToolBOX I Kisil, GG Calvi, BS Dees, DP Mandic arXiv preprint arXiv:2111.15662, 2021 | 13 | 2021 |
| Tensor decompositions and practical applications: A hands-on tutorial I Kisil, GG Calvi, B Scalzo Dees, DP Mandic Recent Trends in Learning From Data: Tutorials from the INNS Big Data and …, 2020 | 11 | 2020 |
| Tensor ensemble learning for multidimensional data I Kisil, A Moniri, DP Mandic 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2018 | 8 | 2018 |
| Understanding the basis of graph signal processing via an intuitive example-driven approach L Stanković, D Mandic, M Daković, I Kisil, E Sejdic, A Constantinides IEEE Signal Processing Magazine 36 (6), 133-145, 2019 | 7 | 2019 |
| Accelerating tensor contraction products via tensor-train decomposition [tips & tricks] I Kisil, GG Calvi, K Konstantinidis, YL Xu, DP Mandic IEEE Signal Processing Magazine 39 (5), 63-70, 2022 | 6 | 2022 |
| Reducing computational complexity of tensor contractions via tensor-train networks I Kisil, GG Calvi, K Konstantinidis, YL Xu, DP Mandic arXiv preprint arXiv:2109.00626, 2021 | 4 | 2021 |
| A class of multidimensional NIPALS algorithms for quaternion and tensor partial least squares regression AE Stott, BS Dees, I Kisil, DP Mandic Signal Processing 160, 316-327, 2019 | 4 | 2019 |
| Refreshing DSP courses through biopresence in the curriculum: A successful paradigm A Moniri, I Kisil, AG Constantinides, DP Mandic 2018 IEEE 23rd International Conference on Digital Signal Processing (DSP), 1-4, 2018 | 4 | 2018 |
| Feature fusion via tensor network summation GG Calvi, I Kisil, DP Mandic 2018 26th European Signal Processing Conference (EUSIPCO), 2623-2627, 2018 | 4 | 2018 |
| An intuitive derivation of the coherence index relation in compressive sensing L Stankovic, D Mandic, M Dakovic, I Kisil arXiv preprint arXiv:1903.11136, 2019 | 2 | 2019 |
| An Example-Driven Introduction to Data Analytics on Graphs L Stankovic, D Mandic, M Dakovic, I Kisil, E Sejdic, AG Constantinides arXiv preprint arXiv:1903.11179, 2019 | 2 | 2019 |
| Tensor decomposition and machine learning for the detection of arteriovenous fistula stenosis: An initial evaluation S Poushpas, P Normahani, I Kisil, B Szubert, DP Mandic, U Jaffer Plos one 18 (7), e0286952, 2023 | 1 | 2023 |
| Higher order tensor decompositions: from intuition to implementation and application I Kisil Imperial College London, 2022 | | 2022 |
| IEEE Proof L Stankovic, DP Mandic, M Dakovic, I Kisil, E Sejdic, AG Constantinides IEEE SIGNAL PROCESSING MAGAZINE 1053 (5888/19), 2019 | | 2019 |
| The sum of tensor networks GG Calvi, I Kisil, DP Mandic arXiv preprint arXiv:1711.00701, 2017 | | 2017 |
