A Technique to Compute Smooth Amplitude, Phase, and Frequency Modulations From the Analytic Signal. - Arun Venkitaraman; Chandra Sekhar Seelamantula (IEEE Signal Process. Lett., 2012)

On Computing Amplitude, Phase, and Frequency Modulations Using a Vector Interpretation of the Analytic Signal. - Arun Venkitaraman; Chandra Sekhar Seelamantula (IEEE Signal Process. Lett., 2013)

Temporal Envelope Fit of Transient Audio Signals. - Arun Venkitaraman; Chandra Sekhar Seelamantula (IEEE Signal Process. Lett., 2013)

Auditory-motivated Gammatone wavelet transform. - Arun Venkitaraman; Aniruddha Adiga; Chandra Sekhar Seelamantula (Signal Process., 2014)

Fractional Hilbert transform extensions and associated analytic signal construction. - Arun Venkitaraman; Chandra Sekhar Seelamantula (Signal Process., 2014)

Binaural Signal Processing Motivated Generalized Analytic Signal Construction and AM-FM Demodulation. - Arun Venkitaraman; Chandra Sekhar Seelamantula (IEEE ACM Trans. Audio Speech Lang. Process., 2014)

Graph linear prediction results in smaller error than standard linear prediction. - Arun Venkitaraman; Saikat Chatterjee; Peter Handel (EUSIPCO, 2015)

Motion-based segmentation of chest and abdomen region of neonates from videos. - Arun Venkitaraman; Vishnu Vardhan Makkapati (ICAPR, 2015)

Hilbert Transform, Analytic Signal, and Modulation Analysis for Graph Signal Processing. - Arun Venkitaraman; Saikat Chatterjee; Peter Händel (CoRR, 2016)

A connectedness constraint for learning sparse graphs. - Martin Sundin; Arun Venkitaraman; Magnus Jansson; Saikat Chatterjee (EUSIPCO, 2017)

Distributed greedy sparse learning over doubly stochastic networks. - Ahmed Zaki; Arun Venkitaraman; Saikat Chatterjee; Lars K. Rasmussen (EUSIPCO, 2017)

Kernel Regression for Signals over Graphs. - Arun Venkitaraman; Saikat Chatterjee; Peter Händel (CoRR, 2017)

Extreme Learning Machine for Graph Signal Processing. - Arun Venkitaraman; Saikat Chatterjee; Peter Handel (EUSIPCO, 2018)

Multi-Kernel Regression for Graph Signal Processing. - Arun Venkitaraman; Saikat Chatterjee; Peter Handel (ICASSP, 2018)

R3Net: Random Weights, Rectifier Linear Units and Robustness for Artificial Neural Network. - Arun Venkitaraman; Alireza M. Javid; Saikat Chatterjee (CoRR, 2018)

Supervised Linear Regression for Graph Learning from Graph Signals. - Arun Venkitaraman; Hermina Petric Maretic; Saikat Chatterjee; Pascal Frossard (CoRR, 2018)

Greedy Sparse Learning Over Network. - Ahmed Zaki; Arun Venkitaraman; Saikat Chatterjee; Lars Kildehoj Rasmussen (IEEE Trans. Signal Inf. Process. over Networks, 2018)

Graph Signal Processing Meets Machine Learning. - Arun Venkitaraman (2018)

Kernel Regression for Graph Signal Prediction in Presence of Sparse Noise. - Arun Venkitaraman; Pascal Frossard; Saikat Chatterjee (ICASSP, 2019)

Learning sparse linear dynamic networks in a hyper-parameter free setting. - Arun Venkitaraman; Håkan Hjalmarsson; Bo Wahlberg (CoRR, 2019)

On Hilbert transform, analytic signal, and modulation analysis for signals over graphs. - Arun Venkitaraman; Saikat Chatterjee; Peter Händel (Signal Process., 2019)

Learning Sparse Graphs for Prediction of Multivariate Data Processes. - Arun Venkitaraman; Dave Zachariah (IEEE Signal Process. Lett., 2019)

Predicting Graph Signals Using Kernel Regression Where the Input Signal is Agnostic to a Graph. - Arun Venkitaraman; Saikat Chatterjee; Peter Händel (IEEE Trans. Signal Inf. Process. over Networks, 2019)

High-Dimensional Neural Feature Using Rectified Linear Unit And Random Matrix Instance. - Alireza M. Javid; Arun Venkitaraman; Mikael Skoglund; Saikat Chatterjee (ICASSP, 2020)

Gaussian Processes Over Graphs. - Arun Venkitaraman; Saikat Chatterjee; Peter Handel (ICASSP, 2020)

Recursive Prediction of Graph Signals With Incoming Nodes. - Arun Venkitaraman; Saikat Chatterjee; Bo Wahlberg (ICASSP, 2020)

On Training and Evaluation of Neural Network Approaches for Model Predictive Control. - Rebecka Winqvist; Arun Venkitaraman; Bo Wahlberg (CoRR, 2020)

Predictive Analysis of COVID-19 Time-series Data from Johns Hopkins University. - Alireza M. Javid; Xinyue Liang; Arun Venkitaraman; Saikat Chatterjee (CoRR, 2020)

Task-similarity Aware Meta-learning through Nonparametric Kernel Regression. - Arun Venkitaraman; Bo Wahlberg (CoRR, 2020)

High-dimensional neural feature design for layer-wise reduction of training cost. - Alireza M. Javid; Arun Venkitaraman; Mikael Skoglund; Saikat Chatterjee (EURASIP J. Adv. Signal Process., 2020)

Learning Models of Model Predictive Controllers using Gradient Data. - Rebecka Winqvist; Arun Venkitaraman; Bo Wahlberg (CoRR, 2021)

Annihilation Filter Approach for Estimating Graph Dynamics from Diffusion Processes. - Arun Venkitaraman; Pascal Frossard (ICASSP, 2022)

Post Hoc Explainability for Time Series Classification: Toward a signal processing perspective. - Rami Mochaourab; Arun Venkitaraman; Isak Samsten; Panagiotis Papapetrou; Cristian R. Rojas (IEEE Signal Process. Mag., 2022)

A Meta-Gnn Approach to Personalized Seizure Detection and Classification. - Abdellah Rahmani; Arun Venkitaraman; Pascal Frossard (ICASSP, 2023)

Knowledge Distillation with Graph Neural Networks for Epileptic Seizure Detection. - Qinyue Zheng; Arun Venkitaraman; Simona Petravic; Pascal Frossard (ECML/PKDD (6), 2023)

Knowledge-Distilled Graph Neural Networks for Personalized Epileptic Seizure Detection. - Qinyue Zheng; Arun Venkitaraman; Simona Petravic; Pascal Frossard (CoRR, 2023)

GraCo - A Graph Composer for Integrated Circuits. - Stefan Uhlich; Andrea Bonetti; Arun Venkitaraman; Ali Momeni 002; Ryoga Matsuo; Chia-Yu Hsieh; Eisaku Ohbuchi; Lorenzo Servadei (CoRR, 2024)

Schemato - An LLM for Netlist-to-Schematic Conversion. - Ryoga Matsuo; Stefan Uhlich; Arun Venkitaraman; Andrea Bonetti; Chia-Yu Hsieh; Ali Momeni 002; Lukas Mauch; Augusto Capone; Eisaku Ohbuchi; Lorenzo Servadei (CoRR, 2024)

Locality-aware Surrogates for Gradient-based Black-box Optimization. - Ali Momeni 002; Stefan Uhlich; Arun Venkitaraman; Chia-Yu Hsieh; Andrea Bonetti; Ryoga Matsuo; Eisaku Ohbuchi; Lorenzo Servadei (CoRR, 2025)

SpiceMixer - Netlist-Level Circuit Evolution. - Stefan Uhlich; Andrea Bonetti; Arun Venkitaraman; Chia-Yu Hsieh; Mustafa Emre Gürsoy; Ryoga Matsuo; Lorenzo Servadei (CoRR, 2025)