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Arun Venkitaraman
Arun Venkitaraman
Senior Research Scientist, Sony AI
Adresse e-mail validée de sony.com
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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
552019
Gaussian processes over graphs
A Venkitaraman, S Chatterjee, P Handel
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
442020
Auditory-motivated Gammatone wavelet transform
A Venkitaraman, A Adiga, CS Seelamantula
Signal Processing 94, 608-619, 2014
352014
Fractional Hilbert transform extensions and associated analytic signal construction
A Venkitaraman, CS Seelamantula
Signal processing 94, 359-372, 2014
332014
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
182017
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
172022
On Hilbert transform, analytic signal, and modulation analysis for signals over graphs
A Venkitaraman, S Chatterjee, P Händel
Signal Processing 156, 106-115, 2019
172019
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
172017
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
152020
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
122023
On Hilbert transform of signals on graphs
A Venkitaraman, S Chatterjee, P Handel
Proc. Sampling Theory Appl, 2015
102015
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
102012
Task-similarity aware meta-learning through nonparametric kernel regression
A Venkitaraman, A Hansson, B Wahlberg
arXiv preprint arXiv:2006.07212, 2020
92020
On training and evaluation of neural network approaches for model predictive control
R Winqvist, A Venkitaraman, B Wahlberg
arXiv preprint arXiv:2005.04112, 2020
92020
Hilbert transform, analytic signal, and modulation analysis for graph signal processing
A Venkitaraman, S Chatterjee, P Händel
arXiv preprint arXiv:1611.05269, 2016
92016
Multi-kernel regression for graph signal processing
A Venkitaraman, S Chatterjee, P Händel
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
82018
Temporal envelope fit of transient audio signals
A Venkitaraman, CS Seelamantula
IEEE Signal Processing Letters 20 (12), 1191-1194, 2013
82013
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
72020
Learning models of model predictive controllers using gradient data
R Winqvist, A Venkitaraman, B Wahlberg
IFAC-PapersOnLine 54 (7), 7-12, 2021
62021
Learning sparse graphs for prediction of multivariate data processes
A Venkitaraman, D Zachariah
IEEE Signal Processing Letters 26 (3), 495-499, 2019
62019
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