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Arun Venkitaraman
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2020 – today
- 2023
- [c13]Abdellah Rahmani, Arun Venkitaraman, Pascal Frossard:
A Meta-Gnn Approach to Personalized Seizure Detection and Classification. ICASSP 2023: 1-5 - [c12]Qinyue Zheng, Arun Venkitaraman, Simona Petravic, Pascal Frossard:
Knowledge Distillation with Graph Neural Networks for Epileptic Seizure Detection. ECML/PKDD (6) 2023: 547-563 - [i17]Qinyue Zheng, Arun Venkitaraman, Simona Petravic, Pascal Frossard:
Knowledge-Distilled Graph Neural Networks for Personalized Epileptic Seizure Detection. CoRR abs/2304.06038 (2023) - 2022
- [j12]Rami Mochaourab
, Arun Venkitaraman, Isak Samsten, Panagiotis Papapetrou, Cristian R. Rojas:
Post Hoc Explainability for Time Series Classification: Toward a signal processing perspective. IEEE Signal Process. Mag. 39(4): 119-129 (2022) - [c11]Arun Venkitaraman, Pascal Frossard:
Annihilation Filter Approach for Estimating Graph Dynamics from Diffusion Processes. ICASSP 2022: 5583-5587 - [i16]Abdellah Rahmani, Arun Venkitaraman, Pascal Frossard:
A Meta-GNN approach to personalized seizure detection and classification. CoRR abs/2211.02642 (2022) - 2021
- [i15]Rebecka Winqvist, Arun Venkitaraman, Bo Wahlberg:
Learning Models of Model Predictive Controllers using Gradient Data. CoRR abs/2102.02173 (2021) - 2020
- [j11]Alireza M. Javid, Arun Venkitaraman, Mikael Skoglund, Saikat Chatterjee:
High-dimensional neural feature design for layer-wise reduction of training cost. EURASIP J. Adv. Signal Process. 2020(1): 40 (2020) - [c10]Alireza M. Javid, Arun Venkitaraman, Mikael Skoglund, Saikat Chatterjee:
High-Dimensional Neural Feature Using Rectified Linear Unit And Random Matrix Instance. ICASSP 2020: 4237-4241 - [c9]Arun Venkitaraman, Saikat Chatterjee, Bo Wahlberg:
Recursive Prediction of Graph Signals With Incoming Nodes. ICASSP 2020: 5565-5569 - [c8]Arun Venkitaraman, Saikat Chatterjee, Peter Handel:
Gaussian Processes Over Graphs. ICASSP 2020: 5640-5644 - [i14]Alireza M. Javid, Arun Venkitaraman, Mikael Skoglund, Saikat Chatterjee:
High-dimensional Neural Feature using Rectified Linear Unit and Random Matrix Instance. CoRR abs/2003.13058 (2020) - [i13]Rebecka Winqvist, Arun Venkitaraman, Bo Wahlberg:
On Training and Evaluation of Neural Network Approaches for Model Predictive Control. CoRR abs/2005.04112 (2020) - [i12]Alireza M. Javid, Xinyue Liang, Arun Venkitaraman, Saikat Chatterjee:
Predictive Analysis of COVID-19 Time-series Data from Johns Hopkins University. CoRR abs/2005.05060 (2020) - [i11]Arun Venkitaraman, Bo Wahlberg:
Task-similarity Aware Meta-learning through Nonparametric Kernel Regression. CoRR abs/2006.07212 (2020)
2010 – 2019
- 2019
- [j10]Arun Venkitaraman
On Hilbert transform, analytic signal, and modulation analysis for signals over graphs. Signal Process. 156: 106-115 (2019) - [j9]Arun Venkitaraman
Learning Sparse Graphs for Prediction of Multivariate Data Processes. IEEE Signal Process. Lett. 26(3): 495-499 (2019) - [j8]Arun Venkitaraman
Predicting Graph Signals Using Kernel Regression Where the Input Signal is Agnostic to a Graph. IEEE Trans. Signal Inf. Process. over Networks 5(4): 698-710 (2019) - [c7]Arun Venkitaraman, Pascal Frossard, Saikat Chatterjee:
Kernel Regression for Graph Signal Prediction in Presence of Sparse Noise. ICASSP 2019: 5426-5430 - [i10]Arun Venkitaraman, Saikat Chatterjee, Bo Wahlberg:
Recursive Prediction of Graph Signals with Incoming Nodes. CoRR abs/1911.11542 (2019) - [i9]Arun Venkitaraman, Håkan Hjalmarsson, Bo Wahlberg:
Learning sparse linear dynamic networks in a hyper-parameter free setting. CoRR abs/1911.11553 (2019) - 2018
- [b1]Arun Venkitaraman:
Graph Signal Processing Meets Machine Learning. Royal Institute of Technology, Stockholm, Sweden, 2018 - [j7]Ahmed Zaki, Arun Venkitaraman
Greedy Sparse Learning Over Network. IEEE Trans. Signal Inf. Process. over Networks 4(3): 424-435 (2018) - [c6]Arun Venkitaraman, Saikat Chatterjee, Peter Handel:
Extreme Learning Machine for Graph Signal Processing. EUSIPCO 2018: 136-140 - [c5]Arun Venkitaraman, Saikat Chatterjee, Peter Handel:
Multi-Kernel Regression for Graph Signal Processing. ICASSP 2018: 4644-4648 - [i8]Arun Venkitaraman, Alireza M. Javid, Saikat Chatterjee:
R3Net: Random Weights, Rectifier Linear Units and Robustness for Artificial Neural Network. CoRR abs/1803.04186 (2018) - [i7]Arun Venkitaraman, Saikat Chatterjee, Peter Händel:
Extreme Learning Machine for Graph Signal Processing. CoRR abs/1803.04193 (2018) - [i6]Arun Venkitaraman, Saikat Chatterjee, Peter Händel:
Multi-kernel Regression For Graph Signal Processing. CoRR abs/1803.04196 (2018) - [i5]Arun Venkitaraman, Saikat Chatterjee, Peter Händel:
Gaussian Processes Over Graphs. CoRR abs/1803.05776 (2018) - [i4]Arun Venkitaraman, Hermina Petric Maretic, Saikat Chatterjee, Pascal Frossard:
Supervised Linear Regression for Graph Learning from Graph Signals. CoRR abs/1811.01586 (2018) - [i3]Arun Venkitaraman, Pascal Frossard, Saikat Chatterjee:
Kernel Regression for Graph Signal Prediction in Presence of Sparse Noise. CoRR abs/1811.02314 (2018) - 2017
- [c4]Martin Sundin, Arun Venkitaraman, Magnus Jansson, Saikat Chatterjee:
A connectedness constraint for learning sparse graphs. EUSIPCO 2017: 151-155 - [c3]Ahmed Zaki, Arun Venkitaraman, Saikat Chatterjee, Lars K. Rasmussen:
Distributed greedy sparse learning over doubly stochastic networks. EUSIPCO 2017: 361-364 - [i2]Arun Venkitaraman, Saikat Chatterjee, Peter Händel:
Kernel Regression for Signals over Graphs. CoRR abs/1706.02191 (2017) - 2016
- [i1]Arun Venkitaraman, Saikat Chatterjee, Peter Händel:
Hilbert Transform, Analytic Signal, and Modulation Analysis for Graph Signal Processing. CoRR abs/1611.05269 (2016) - 2015
- [c2]Arun Venkitaraman, Saikat Chatterjee, Peter Handel:
Graph linear prediction results in smaller error than standard linear prediction. EUSIPCO 2015: 220-224 - [c1]Arun Venkitaraman, Vishnu Vardhan Makkapati
Motion-based segmentation of chest and abdomen region of neonates from videos. ICAPR 2015: 1-5 - 2014
- [j6]Arun Venkitaraman, Chandra Sekhar Seelamantula:
Fractional Hilbert transform extensions and associated analytic signal construction. Signal Process. 94: 359-372 (2014) - [j5]Arun Venkitaraman, Aniruddha Adiga, Chandra Sekhar Seelamantula:
Auditory-motivated Gammatone wavelet transform. Signal Process. 94: 608-619 (2014) - [j4]Arun Venkitaraman, Chandra Sekhar Seelamantula:
Binaural Signal Processing Motivated Generalized Analytic Signal Construction and AM-FM Demodulation. IEEE ACM Trans. Audio Speech Lang. Process. 22(6): 1023-1036 (2014) - 2013
- [j3]Arun Venkitaraman, Chandra Sekhar Seelamantula:
On Computing Amplitude, Phase, and Frequency Modulations Using a Vector Interpretation of the Analytic Signal. IEEE Signal Process. Lett. 20(12): 1187-1190 (2013) - [j2]Arun Venkitaraman, Chandra Sekhar Seelamantula:
Temporal Envelope Fit of Transient Audio Signals. IEEE Signal Process. Lett. 20(12): 1191-1194 (2013) - 2012
- [j1]Arun Venkitaraman, Chandra Sekhar Seelamantula:
A Technique to Compute Smooth Amplitude, Phase, and Frequency Modulations From the Analytic Signal. IEEE Signal Process. Lett. 19(10): 623-626 (2012)
Coauthor Index
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