Arun Venkitaraman

ORCID

Publication Activity (10 Years)

Years Active: 2012-2023
Publications (10 Years): 34

Top Venues

CoRR

ICASSP

EUSIPCO

IEEE Signal Process. Lett.

Royal Institute of Technology, Stockholm, Sweden (PHD)

Education History

Royal Institute of Technology, Stockholm, Sweden

PHD

Publications

Abdellah Rahmani, Arun Venkitaraman, Pascal Frossard
A Meta-Gnn Approach to Personalized Seizure Detection and Classification. ICASSP (2023)
Qinyue Zheng, Arun Venkitaraman, Simona Petravic, Pascal Frossard
Knowledge Distillation with Graph Neural Networks for Epileptic Seizure Detection. ECML/PKDD (6) (2023)
Qinyue Zheng, Arun Venkitaraman, Simona Petravic, Pascal Frossard
Knowledge-Distilled Graph Neural Networks for Personalized Epileptic Seizure Detection. CoRR (2023)
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) (2022)
Arun Venkitaraman, Pascal Frossard
Annihilation Filter Approach for Estimating Graph Dynamics from Diffusion Processes. ICASSP (2022)
Abdellah Rahmani, Arun Venkitaraman, Pascal Frossard
A Meta-GNN approach to personalized seizure detection and classification. CoRR (2022)
Rebecka Winqvist, Arun Venkitaraman, Bo Wahlberg
Learning Models of Model Predictive Controllers using Gradient Data. CoRR (2021)
Alireza M. Javid, Arun Venkitaraman, Mikael Skoglund, Saikat Chatterjee
High-dimensional Neural Feature using Rectified Linear Unit and Random Matrix Instance. CoRR (2020)
Alireza M. Javid, Xinyue Liang, Arun Venkitaraman, Saikat Chatterjee
Predictive Analysis of COVID-19 Time-series Data from Johns Hopkins University. CoRR (2020)
Arun Venkitaraman, Saikat Chatterjee, Bo Wahlberg
Recursive Prediction of Graph Signals With Incoming Nodes. ICASSP (2020)
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) (2020)
Alireza M. Javid, Arun Venkitaraman, Mikael Skoglund, Saikat Chatterjee
High-Dimensional Neural Feature Using Rectified Linear Unit And Random Matrix Instance. ICASSP (2020)
Rebecka Winqvist, Arun Venkitaraman, Bo Wahlberg
On Training and Evaluation of Neural Network Approaches for Model Predictive Control. CoRR (2020)
Arun Venkitaraman, Bo Wahlberg
Task-similarity Aware Meta-learning through Nonparametric Kernel Regression. CoRR (2020)
Arun Venkitaraman, Saikat Chatterjee, Peter Handel
Gaussian Processes Over Graphs. ICASSP (2020)
Arun Venkitaraman, Saikat Chatterjee, Bo Wahlberg
Recursive Prediction of Graph Signals with Incoming Nodes. CoRR (2019)
Arun Venkitaraman, Saikat Chatterjee, Peter Händel
Predicting Graph Signals Using Kernel Regression Where the Input Signal is Agnostic to a Graph. IEEE Trans. Signal Inf. Process. over Networks 5 (4) (2019)
Arun Venkitaraman, Pascal Frossard, Saikat Chatterjee
Kernel Regression for Graph Signal Prediction in Presence of Sparse Noise. ICASSP (2019)
Arun Venkitaraman, Saikat Chatterjee, Peter Händel
On Hilbert transform, analytic signal, and modulation analysis for signals over graphs. Signal Process. 156 (2019)
Arun Venkitaraman, Håkan Hjalmarsson, Bo Wahlberg
Learning sparse linear dynamic networks in a hyper-parameter free setting. CoRR (2019)
Arun Venkitaraman, Dave Zachariah
Learning Sparse Graphs for Prediction of Multivariate Data Processes. IEEE Signal Process. Lett. 26 (3) (2019)
Arun Venkitaraman, Saikat Chatterjee, Peter Händel
Gaussian Processes Over Graphs. CoRR (2018)
Arun Venkitaraman, Saikat Chatterjee, Peter Handel
Multi-Kernel Regression for Graph Signal Processing. ICASSP (2018)
Arun Venkitaraman, Pascal Frossard, Saikat Chatterjee
Kernel Regression for Graph Signal Prediction in Presence of Sparse Noise. CoRR (2018)
Arun Venkitaraman, Saikat Chatterjee, Peter Händel
Multi-kernel Regression For Graph Signal Processing. CoRR (2018)
Ahmed Zaki, Arun Venkitaraman, Saikat Chatterjee, Lars Kildehoj Rasmussen
Greedy Sparse Learning Over Network. IEEE Trans. Signal Inf. Process. over Networks 4 (3) (2018)
Arun Venkitaraman, Saikat Chatterjee, Peter Händel
Extreme Learning Machine for Graph Signal Processing. CoRR (2018)
Arun Venkitaraman, Alireza M. Javid, Saikat Chatterjee
R3Net: Random Weights, Rectifier Linear Units and Robustness for Artificial Neural Network. CoRR (2018)
Arun Venkitaraman, Hermina Petric Maretic, Saikat Chatterjee, Pascal Frossard
Supervised Linear Regression for Graph Learning from Graph Signals. CoRR (2018)
Arun Venkitaraman, Saikat Chatterjee, Peter Handel
Extreme Learning Machine for Graph Signal Processing. EUSIPCO (2018)
Martin Sundin, Arun Venkitaraman, Magnus Jansson, Saikat Chatterjee
A connectedness constraint for learning sparse graphs. EUSIPCO (2017)
Ahmed Zaki, Arun Venkitaraman, Saikat Chatterjee, Lars K. Rasmussen
Distributed greedy sparse learning over doubly stochastic networks. EUSIPCO (2017)
Arun Venkitaraman, Saikat Chatterjee, Peter Händel
Kernel Regression for Signals over Graphs. CoRR (2017)
Arun Venkitaraman, Saikat Chatterjee, Peter Händel
Hilbert Transform, Analytic Signal, and Modulation Analysis for Graph Signal Processing. CoRR (2016)
Arun Venkitaraman, Vishnu Vardhan Makkapati
Motion-based segmentation of chest and abdomen region of neonates from videos. ICAPR (2015)
Arun Venkitaraman, Saikat Chatterjee, Peter Handel
Graph linear prediction results in smaller error than standard linear prediction. EUSIPCO (2015)
Arun Venkitaraman, Aniruddha Adiga, Chandra Sekhar Seelamantula
Auditory-motivated Gammatone wavelet transform. Signal Process. 94 (2014)
Arun Venkitaraman, Chandra Sekhar Seelamantula
Fractional Hilbert transform extensions and associated analytic signal construction. Signal Process. 94 (2014)
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) (2014)
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) (2013)
Arun Venkitaraman, Chandra Sekhar Seelamantula
Temporal Envelope Fit of Transient Audio Signals. IEEE Signal Process. Lett. 20 (12) (2013)
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) (2012)

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Publication Activity (10 Years)

Top Topics

Top Venues

Arun Venkitaraman