Vivek Sivaraman Narayanaswamy

47 papers A* 6A 2B 1C 1Misc 7Journal 20Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	The Anatomy of Uncertainty in LLMs. CoRR Aditya Taparia, Ransalu Senanayake, Kowshik Thopalli, Vivek Sivaraman Narayanaswamy
2025	J	`jnl`	Interpretable and Steerable Concept Bottleneck Sparse Autoencoders. CoRR Akshay Kulkarni, Tsui-Wei Weng, Vivek Sivaraman Narayanaswamy, Shusen Liu, Wesam A. Sakla, Kowshik Thopalli
2025	Misc	`conf`	Leveraging Registers in Vision Transformers for Robust Adaptation. ICASSP Srikar Yellapragada, Kowshik Thopalli, Vivek Sivaraman Narayanaswamy, Wesam A. Sakla, Yang Liu, Yamen Mubarka, Dimitris Samaras, Jayaraman J. Thiagarajan
2025	J	`jnl`	Leveraging Registers in Vision Transformers for Robust Adaptation. CoRR Srikar Yellapragada, Kowshik Thopalli, Vivek Sivaraman Narayanaswamy, Wesam A. Sakla, Yang Liu, Yamen Mubarka, Dimitris Samaras, Jayaraman J. Thiagarajan
2025	—	`conf`	The Surprising Utility of Group Partitioning in Improving Conformal Prediction of Visual Classifiers under Distributional Shifts. CVPR Workshops Kowshik Thopalli, Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan
2024	—	`conf`	DECIDER: Leveraging Foundation Model Priors for Improved Model Failure Detection and Explanation. ECCV (79) Rakshith Subramanyam, Kowshik Thopalli, Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan
2024	J	`jnl`	DECIDER: Leveraging Foundation Model Priors for Improved Model Failure Detection and Explanation. CoRR Rakshith Subramanyam, Kowshik Thopalli, Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan
2024	A*	`conf`	On the Use of Anchoring for Training Vision Models. NeurIPS Vivek Sivaraman Narayanaswamy, Kowshik Thopalli, Rushil Anirudh, Yamen Mubarka, Wesam A. Sakla, Jayaraman J. Thiagarajan
2024	J	`jnl`	On the Use of Anchoring for Training Vision Models. CoRR Vivek Sivaraman Narayanaswamy, Kowshik Thopalli, Rushil Anirudh, Yamen Mubarka, Wesam A. Sakla, Jayaraman J. Thiagarajan
2024	A*	`conf`	PAGER: Accurate Failure Characterization in Deep Regression Models. ICML Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Puja Trivedi, Rushil Anirudh
2024	Misc	`conf`	The Double-Edged Sword Of Ai Safety: Balancing Anomaly Detection and OOD Generalization Via Model Anchoring. ICASSP Vivek Sivaraman Narayanaswamy, Rushil Anirudh, Jayaraman J. Thiagarajan
2023	B	`conf`	AN L2-Normalized Spatial Attention Network for Accurate and Fast Classification of Brain Tumors in 2D T1-Weighted CE-MRI Images. ICIP Grace Billingsley, Julia Dietlmeier, Vivek Sivaraman Narayanaswamy, Andreas Spanias, Noel E. O'Connor
2023	J	`jnl`	An L2-Normalized Spatial Attention Network For Accurate And Fast Classification Of Brain Tumors In 2D T1-Weighted CE-MRI Images. CoRR Grace Billingsley, Julia Dietlmeier, Vivek Sivaraman Narayanaswamy, Andreas Spanias, Noel E. O'Connor
2023	—	`conf`	Exploring Inlier and Outlier Specification for Improved Medical OOD Detection. ICCV (Workshops) Vivek Sivaraman Narayanaswamy, Yamen Mubarka, Rushil Anirudh, Deepta Rajan, Jayaraman J. Thiagarajan
2023	—	`conf`	Know Your Space: Inlier and Outlier Construction for Calibrating Medical OOD Detectors. MIDL Vivek Sivaraman Narayanaswamy, Yamen Mubarka, Rushil Anirudh, Deepta Rajan, Andreas Spanias, Jayaraman J. Thiagarajan
2023	J	`jnl`	Optimizing Solar Power Using Array Topology Reconfiguration With Regularized Deep Neural Networks. IEEE Access Vivek Sivaraman Narayanaswamy, Raja Ayyanar, Cihan Tepedelenlioglu, Devarajan Srinivasan, Andreas Spanias
2023	J	`jnl`	PAGER: A Framework for Failure Analysis of Deep Regression Models. CoRR Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Puja Trivedi, Rushil Anirudh
2023	Misc	`conf`	Signal Analysis-Synthesis Using the Quantum Fourier Transform. ICASSP Aradhita Sharma, Glen S. Uehara, Vivek Sivaraman Narayanaswamy, Leslie Miller, Andreas Spanias
2022	A*	`conf`	Improved StyleGAN-v2 based Inversion for Out-of-Distribution Images. ICML Rakshith Subramanyam, Vivek Sivaraman Narayanaswamy, Mark Naufel, Andreas Spanias, Jayaraman J. Thiagarajan
2022	J	`jnl`	Instruction Tools for Signal Processing and Machine Learning for Ion-Channel Sensors. Int. J. Virtual Pers. Learn. Environ. 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
2022	Misc	`conf`	Predicting the Generalization Gap in Deep Models using Anchoring. ICASSP Vivek Sivaraman Narayanaswamy, Rushil Anirudh, Irene Kim, Yamen Mubarka, Andreas Spanias, Jayaraman J. Thiagarajan
2022	—	`conf`	Quantum Machine Learning for Photovoltaic Topology Optimization. IISA Glen S. Uehara, Vivek Sivaraman Narayanaswamy, Cihan Tepedelenlioglu, Andreas Spanias
2022	J	`jnl`	Revisiting Inlier and Outlier Specification for Improved Out-of-Distribution Detection. CoRR Vivek Sivaraman Narayanaswamy, Yamen Mubarka, Rushil Anirudh, Deepta Rajan, Andreas Spanias, Jayaraman J. Thiagarajan
2022	A*	`conf`	Single Model Uncertainty Estimation via Stochastic Data Centering. NeurIPS Jayaraman J. Thiagarajan, Rushil Anirudh, Vivek Sivaraman Narayanaswamy, Timo Bremer
2022	J	`jnl`	Single Model Uncertainty Estimation via Stochastic Data Centering. CoRR Jayaraman J. Thiagarajan, Rushil Anirudh, Vivek Sivaraman Narayanaswamy, Peer-Timo Bremer
2022	—	`conf`	The ASU-DCU International Research and Workforce Development Program on Sensors and Machine Learning. IISA 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
2021	A*	`conf`	Accurate and Robust Feature Importance Estimation under Distribution Shifts. AAAI Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Rushil Anirudh, Peer-Timo Bremer, Andreas Spanias
2021	—	`conf`	COVID-19 Detection using Audio Spectral Features and Machine Learning. ACSCC Michael Esposito, Sunil Rao, Vivek Sivaraman Narayanaswamy, Andreas Spanias
2021	J	`jnl`	COVID-19 detection using cough sound analysis and deep learning algorithms. Intell. Decis. Technol. Sunil Rao, Vivek Sivaraman Narayanaswamy, Michael Esposito, Jayaraman J. Thiagarajan, Andreas Spanias
2021	—	`conf`	Deep Learning with hyper-parameter tuning for COVID-19 Cough Detection. IISA Sunil Rao, Vivek Sivaraman Narayanaswamy, Michael Esposito, Jayaraman J. Thiagarajan, Andreas Spanias
2021	A*	`conf`	Designing Counterfactual Generators using Deep Model Inversion. NeurIPS Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Deepta Rajan, Jason Liang, Akshay Chaudhari, Andreas Spanias
2021	J	`jnl`	Designing Counterfactual Generators using Deep Model Inversion. CoRR Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Deepta Rajan, Jason Liang, Akshay Chaudhari, Andreas Spanias
2021	C	`conf`	Experiences with Web-based Signal Analysis Laboratories and Online Training during the COVID-19 Period. FIE Vivek Sivaraman Narayanaswamy, Photini Spanias, Sunil Rao, Andreas Spanias
2021	J	`jnl`	Loss Estimators Improve Model Generalization. CoRR Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Deepta Rajan, Andreas Spanias
2021	A	`conf`	On the Design of Deep Priors for Unsupervised Audio Restoration. Interspeech Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Andreas Spanias
2021	J	`jnl`	On the Design of Deep Priors for Unsupervised Audio Restoration. CoRR Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Andreas Spanias
2021	Misc	`conf`	Using Deep Image Priors to Generate Counterfactual Explanations. ICASSP Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Andreas Spanias
2020	J	`jnl`	Accurate and Robust Feature Importance Estimation under Distribution Shifts. CoRR Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Rushil Anirudh, Peer-Timo Bremer, Andreas Spanias
2020	—	`book`	Machine Learning for Solar Array Monitoring, Optimization, and Control Sunil Rao, Sameeksha Katoch, Vivek Sivaraman Narayanaswamy, Gowtham Muniraju, Cihan Tepedelenlioglu, Andreas Spanias, Pavan K. Turaga, Raja Ayyanar, Devarajan Srinivasan
2020	A	`conf`	Unsupervised Audio Source Separation Using Generative Priors. INTERSPEECH Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Rushil Anirudh, Andreas Spanias
2020	J	`jnl`	Unsupervised Audio Source Separation using Generative Priors. CoRR Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Rushil Anirudh, Andreas Spanias
2020	J	`jnl`	Using Deep Image Priors to Generate Counterfactual Explanations. CoRR Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Andreas Spanias
2019	J	`jnl`	Audio Source Separation via Multi-Scale Learning with Dilated Dense U-Nets. CoRR Vivek Sivaraman Narayanaswamy, Sameeksha Katoch, Jayaraman J. Thiagarajan, Huan Song, Andreas Spanias
2019	—	`conf`	Connection Topology Optimization in Photovoltaic Arrays using Neural Networks. ICPS Vivek Sivaraman Narayanaswamy, Raja Ayyanar, Andreas Spanias, Cihan Tepedelenlioglu, Devarajan Srinivasan
2019	Misc	`conf`	Designing an Effective Metric Learning Pipeline for Speaker Diarization. ICASSP Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Huan Song, Andreas Spanias
2019	Misc	`conf`	Introducing Machine Learning in Undergraduate DSP Classes. ICASSP Uday Shankar Shanthamallu, Sunil Rao, Abhinav Dixit, Vivek Sivaraman Narayanaswamy, Jie Fan, Andreas Spanias
2018	J	`jnl`	Designing an Effective Metric Learning Pipeline for Speaker Diarization. CoRR Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Huan Song, Andreas Spanias