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ORCIDVivek Sivaraman Narayanaswamy
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Books and Theses
- 2020
[b1]Sunil Rao, Sameeksha Katoch, Vivek Sivaraman Narayanaswamy, Gowtham Muniraju, Cihan Tepedelenlioglu, Andreas Spanias, Pavan K. Turaga, Raja Ayyanar, Devarajan Srinivasan
:
Machine Learning for Solar Array Monitoring, Optimization, and Control. Synthesis Lectures on Power Electronics, Morgan & Claypool Publishers 2020, ISBN 978-3-031-01377-5
Journal Articles
- 2023
- [j3]Vivek Sivaraman Narayanaswamy, Raja Ayyanar, Cihan Tepedelenlioglu, Devarajan Srinivasan, Andreas Spanias:
Optimizing Solar Power Using Array Topology Reconfiguration With Regularized Deep Neural Networks. IEEE Access 11: 7461-7470 (2023) - 2022
- [j2]Prasanna Sattigeri, Jayaraman J. Thiagarajan, Karthikeyan Ramamurthy, Andreas Spanias, Mahesh K. Banavar, Abhinav Dixit, Jie Fan, Mohit Malu, Kristen Jaskie, Sunil Rao, Uday Shankar Shanthamallu, Vivek Sivaraman Narayanaswamy, Sameeksha Katoch:
Instruction Tools for Signal Processing and Machine Learning for Ion-Channel Sensors. Int. J. Virtual Pers. Learn. Environ. 12(1): 1-17 (2022) - 2021
- [j1]Sunil Rao, Vivek Sivaraman Narayanaswamy, Michael Esposito, Jayaraman J. Thiagarajan, Andreas Spanias:
COVID-19 detection using cough sound analysis and deep learning algorithms. Intell. Decis. Technol. 15(4): 655-665 (2021)
Conference and Workshop Papers
- 2024
- [c23]Rakshith Subramanyam, Kowshik Thopalli, Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan:
DECIDER: Leveraging Foundation Model Priors for Improved Model Failure Detection and Explanation. ECCV (79) 2024: 465-482 - [c22]Vivek Sivaraman Narayanaswamy, Rushil Anirudh, Jayaraman J. Thiagarajan:
The Double-Edged Sword Of Ai Safety: Balancing Anomaly Detection and OOD Generalization Via Model Anchoring. ICASSP 2024: 7235-7239 - [c21]Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Puja Trivedi, Rushil Anirudh:
PAGER: Accurate Failure Characterization in Deep Regression Models. ICML 2024 - 2023
- [c20]Aradhita Sharma, Glen S. Uehara, Vivek Sivaraman Narayanaswamy, Leslie Miller, Andreas Spanias:
Signal Analysis-Synthesis Using the Quantum Fourier Transform. ICASSP 2023: 1-5 - [c19]Vivek Sivaraman Narayanaswamy, Yamen Mubarka, Rushil Anirudh, Deepta Rajan, Jayaraman J. Thiagarajan:
Exploring Inlier and Outlier Specification for Improved Medical OOD Detection. ICCV (Workshops) 2023: 4591-4600 - [c18]Grace Billingsley, Julia Dietlmeier, Vivek Sivaraman Narayanaswamy, Andreas Spanias, Noel E. O'Connor:
AN L2-Normalized Spatial Attention Network for Accurate and Fast Classification of Brain Tumors in 2D T1-Weighted CE-MRI Images. ICIP 2023: 1895-1899 - [c17]Vivek Sivaraman Narayanaswamy, Yamen Mubarka, Rushil Anirudh, Deepta Rajan, Andreas Spanias, Jayaraman J. Thiagarajan:
Know Your Space: Inlier and Outlier Construction for Calibrating Medical OOD Detectors. MIDL 2023: 190-211 - 2022
- [c16]Vivek Sivaraman Narayanaswamy, Rushil Anirudh, Irene Kim, Yamen Mubarka, Andreas Spanias, Jayaraman J. Thiagarajan:
Predicting the Generalization Gap in Deep Models using Anchoring. ICASSP 2022: 4393-4397 - [c15]Rakshith Subramanyam, Vivek Sivaraman Narayanaswamy, Mark Naufel, Andreas Spanias, Jayaraman J. Thiagarajan:
Improved StyleGAN-v2 based Inversion for Out-of-Distribution Images. ICML 2022: 20625-20639 - [c14]Andreas Spanias, Vivek Sivaraman Narayanaswamy, Erica Forzani, Gregory B. Raupp, Nadia N. Kellam, Megan O'Donnell, Wendy Barnard, Jean S. Larson, Noel E. O'Connor, Nicholas Dunne, Stephen Daniels, Suzanne Little:
The ASU-DCU International Research and Workforce Development Program on Sensors and Machine Learning. IISA 2022: 1-6 - [c13]Glen S. Uehara, Vivek Sivaraman Narayanaswamy, Cihan Tepedelenlioglu, Andreas Spanias:
Quantum Machine Learning for Photovoltaic Topology Optimization. IISA 2022: 1-5 - [c12]Jayaraman J. Thiagarajan, Rushil Anirudh, Vivek Sivaraman Narayanaswamy, Timo Bremer:
Single Model Uncertainty Estimation via Stochastic Data Centering. NeurIPS 2022 - 2021
- [c11]Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Rushil Anirudh, Peer-Timo Bremer, Andreas Spanias:
Accurate and Robust Feature Importance Estimation under Distribution Shifts. AAAI 2021: 7891-7898 - [c10]Michael Esposito, Sunil Rao, Vivek Sivaraman Narayanaswamy, Andreas Spanias:
COVID-19 Detection using Audio Spectral Features and Machine Learning. ACSCC 2021: 1146-1150 - [c9]Vivek Sivaraman Narayanaswamy, Photini Spanias, Sunil Rao, Andreas Spanias:
Experiences with Web-based Signal Analysis Laboratories and Online Training during the COVID-19 Period. FIE 2021: 1-4 - [c8]Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Andreas Spanias:
Using Deep Image Priors to Generate Counterfactual Explanations. ICASSP 2021: 2770-2774 - [c7]Sunil Rao, Vivek Sivaraman Narayanaswamy, Michael Esposito, Jayaraman J. Thiagarajan, Andreas Spanias:
Deep Learning with hyper-parameter tuning for COVID-19 Cough Detection. IISA 2021: 1-5 - [c6]Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Andreas Spanias:
On the Design of Deep Priors for Unsupervised Audio Restoration. Interspeech 2021: 2167-2171 - [c5]Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Deepta Rajan, Jia Liang, Akshay Chaudhari, Andreas Spanias:
Designing Counterfactual Generators using Deep Model Inversion. NeurIPS 2021: 16873-16884 - 2020
- [c4]Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Rushil Anirudh, Andreas Spanias:
Unsupervised Audio Source Separation Using Generative Priors. INTERSPEECH 2020: 2657-2661 - 2019
- [c3]Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Huan Song, Andreas Spanias:
Designing an Effective Metric Learning Pipeline for Speaker Diarization. ICASSP 2019: 5806-5810 - [c2]Uday Shankar Shanthamallu, Sunil Rao, Abhinav Dixit, Vivek Sivaraman Narayanaswamy, Jie Fan, Andreas Spanias:
Introducing Machine Learning in Undergraduate DSP Classes. ICASSP 2019: 7655-7659 - [c1]Vivek Sivaraman Narayanaswamy, Raja Ayyanar, Andreas Spanias, Cihan Tepedelenlioglu, Devarajan Srinivasan:
Connection Topology Optimization in Photovoltaic Arrays using Neural Networks. ICPS 2019: 167-172
Informal and Other Publications
- 2024
- [i14]Vivek Sivaraman Narayanaswamy, Kowshik Thopalli, Rushil Anirudh, Yamen Mubarka, Wesam Sakla, Jayaraman J. Thiagarajan:
On the Use of Anchoring for Training Vision Models. CoRR abs/2406.00529 (2024) - [i13]Rakshith Subramanyam, Kowshik Thopalli, Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan:
DECIDER: Leveraging Foundation Model Priors for Improved Model Failure Detection and Explanation. CoRR abs/2408.00331 (2024) - 2023
- [i12]Grace Billingsley, Julia Dietlmeier, Vivek Sivaraman Narayanaswamy, Andreas Spanias, Noel E. O'Connor:
An L2-Normalized Spatial Attention Network For Accurate And Fast Classification Of Brain Tumors In 2D T1-Weighted CE-MRI Images. CoRR abs/2308.00491 (2023) - [i11]Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Puja Trivedi, Rushil Anirudh:
PAGER: A Framework for Failure Analysis of Deep Regression Models. CoRR abs/2309.10977 (2023) - 2022
- [i10]Vivek Sivaraman Narayanaswamy, Yamen Mubarka, Rushil Anirudh, Deepta Rajan, Andreas Spanias, Jayaraman J. Thiagarajan:
Revisiting Inlier and Outlier Specification for Improved Out-of-Distribution Detection. CoRR abs/2207.05286 (2022) - [i9]Jayaraman J. Thiagarajan, Rushil Anirudh, Vivek Sivaraman Narayanaswamy, Peer-Timo Bremer:
Single Model Uncertainty Estimation via Stochastic Data Centering. CoRR abs/2207.07235 (2022) - 2021
- [i8]Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Deepta Rajan, Andreas Spanias:
Loss Estimators Improve Model Generalization. CoRR abs/2103.03788 (2021) - [i7]Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Andreas Spanias:
On the Design of Deep Priors for Unsupervised Audio Restoration. CoRR abs/2104.07161 (2021) - [i6]Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Deepta Rajan, Jason Liang, Akshay Chaudhari, Andreas Spanias:
Designing Counterfactual Generators using Deep Model Inversion. CoRR abs/2109.14274 (2021) - 2020
- [i5]Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Rushil Anirudh, Andreas Spanias:
Unsupervised Audio Source Separation using Generative Priors. CoRR abs/2005.13769 (2020) - [i4]Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Rushil Anirudh, Peer-Timo Bremer, Andreas Spanias:
Accurate and Robust Feature Importance Estimation under Distribution Shifts. CoRR abs/2009.14454 (2020) - [i3]Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Andreas Spanias:
Using Deep Image Priors to Generate Counterfactual Explanations. CoRR abs/2010.12046 (2020) - 2019
- [i2]Vivek Sivaraman Narayanaswamy, Sameeksha Katoch, Jayaraman J. Thiagarajan, Huan Song, Andreas Spanias:
Audio Source Separation via Multi-Scale Learning with Dilated Dense U-Nets. CoRR abs/1904.04161 (2019) - 2018
- [i1]Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Huan Song, Andreas Spanias:
Designing an Effective Metric Learning Pipeline for Speaker Diarization. CoRR abs/1811.00183 (2018)
Coauthor Index
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