| Predicting graph signals using kernel regression where the input signal is agnostic to a graph A Venkitaraman, S Chatterjee, P Händel IEEE Transactions on Signal and Information Processing over Networks 5 (4 …, 2019 | 53 | 2019 |
| Gaussian processes over graphs A Venkitaraman, S Chatterjee, P Handel ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 44 | 2020 |
| Auditory-motivated Gammatone wavelet transform A Venkitaraman, A Adiga, CS Seelamantula Signal Processing 94, 608-619, 2014 | 35 | 2014 |
| Fractional Hilbert transform extensions and associated analytic signal construction A Venkitaraman, CS Seelamantula Signal processing 94, 359-372, 2014 | 33 | 2014 |
| A connectedness constraint for learning sparse graphs M Sundin, A Venkitaraman, M Jansson, S Chatterjee 2017 25th European Signal Processing Conference (EUSIPCO), 151-155, 2017 | 18 | 2017 |
| Post hoc explainability for time series classification: Toward a signal processing perspective R Mochaourab, A Venkitaraman, I Samsten, P Papapetrou, CR Rojas IEEE signal processing magazine 39 (4), 119-129, 2022 | 17 | 2022 |
| Greedy sparse learning over network A Zaki, A Venkitaraman, S Chatterjee, LK Rasmussen IEEE Transactions on Signal and Information Processing over Networks 4 (3 …, 2017 | 16 | 2017 |
| Predictive analysis of COVID-19 time-series data from Johns Hopkins University AM Javid, X Liang, A Venkitaraman, S Chatterjee arXiv preprint arXiv:2005.05060, 2020 | 15 | 2020 |
| On Hilbert transform, analytic signal, and modulation analysis for signals over graphs A Venkitaraman, S Chatterjee, P Händel Signal Processing 156, 106-115, 2019 | 15 | 2019 |
| A Meta-GNN approach to personalized seizure detection and classification A Rahmani, A Venkitaraman, P Frossard ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 11 | 2023 |
| On Hilbert transform of signals on graphs A Venkitaraman, S Chatterjee, P Handel Proc. Sampling Theory Appl, 2015 | 10 | 2015 |
| A technique to compute smooth amplitude, phase, and frequency modulations from the analytic signal A Venkitaraman, CS Seelamantula IEEE Signal Processing Letters 19 (10), 623-626, 2012 | 10 | 2012 |
| Task-similarity aware meta-learning through nonparametric kernel regression A Venkitaraman, A Hansson, B Wahlberg arXiv preprint arXiv:2006.07212, 2020 | 9 | 2020 |
| On training and evaluation of neural network approaches for model predictive control R Winqvist, A Venkitaraman, B Wahlberg arXiv preprint arXiv:2005.04112, 2020 | 9 | 2020 |
| Hilbert transform, analytic signal, and modulation analysis for graph signal processing A Venkitaraman, S Chatterjee, P Händel arXiv preprint arXiv:1611.05269, 2016 | 9 | 2016 |
| Multi-kernel regression for graph signal processing A Venkitaraman, S Chatterjee, P Händel 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 8 | 2018 |
| Temporal envelope fit of transient audio signals A Venkitaraman, CS Seelamantula IEEE Signal Processing Letters 20 (12), 1191-1194, 2013 | 8 | 2013 |
| Recursive prediction of graph signals with incoming nodes A Venkitaraman, S Chatterjee, B Wahlberg ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 7 | 2020 |
| Learning models of model predictive controllers using gradient data R Winqvist, A Venkitaraman, B Wahlberg IFAC-PapersOnLine 54 (7), 7-12, 2021 | 6 | 2021 |
| Learning sparse graphs for prediction of multivariate data processes A Venkitaraman, D Zachariah IEEE Signal Processing Letters 26 (3), 495-499, 2019 | 6 | 2019 |
Saikat ChatterjeeKTH - Royal Institute of TechnologyVerified email at kth.se
