Designing an Effective Metric Learning Pipeline for Speaker Diarization. - Vivek Sivaraman Narayanaswamy; Jayaraman J. Thiagarajan; Huan Song; Andreas Spanias (ICASSP, 2019)

Introducing Machine Learning in Undergraduate DSP Classes. - Uday Shankar Shanthamallu; Sunil Rao; Abhinav Dixit; Vivek Sivaraman Narayanaswamy; Jie Fan; Andreas Spanias (ICASSP, 2019)

Connection Topology Optimization in Photovoltaic Arrays using Neural Networks. - Vivek Sivaraman Narayanaswamy; Raja Ayyanar 001; Andreas Spanias; Cihan Tepedelenlioglu; Devarajan Srinivasan (ICPS, 2019)

Audio Source Separation via Multi-Scale Learning with Dilated Dense U-Nets. - Vivek Sivaraman Narayanaswamy; Sameeksha Katoch; Jayaraman J. Thiagarajan; Huan Song; Andreas Spanias (CoRR, 2019)

Unsupervised Audio Source Separation Using Generative Priors. - Vivek Sivaraman Narayanaswamy; Jayaraman J. Thiagarajan; Rushil Anirudh; Andreas Spanias (INTERSPEECH, 2020)

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 001; Devarajan Srinivasan (Morgan & Claypool Publishers, 2020)

Accurate and Robust Feature Importance Estimation under Distribution Shifts. - Jayaraman J. Thiagarajan; Vivek Sivaraman Narayanaswamy; Rushil Anirudh; Peer-Timo Bremer; Andreas Spanias (AAAI, 2021)

COVID-19 Detection using Audio Spectral Features and Machine Learning. - Michael Esposito; Sunil Rao; Vivek Sivaraman Narayanaswamy; Andreas Spanias (ACSCC, 2021)

Experiences with Web-based Signal Analysis Laboratories and Online Training during the COVID-19 Period. - Vivek Sivaraman Narayanaswamy; Photini Spanias; Sunil Rao; Andreas Spanias (FIE, 2021)

Using Deep Image Priors to Generate Counterfactual Explanations. - Vivek Sivaraman Narayanaswamy; Jayaraman J. Thiagarajan; Andreas Spanias (ICASSP, 2021)

Deep Learning with hyper-parameter tuning for COVID-19 Cough Detection. - Sunil Rao; Vivek Sivaraman Narayanaswamy; Michael Esposito; Jayaraman J. Thiagarajan; Andreas Spanias (IISA, 2021)

On the Design of Deep Priors for Unsupervised Audio Restoration. - Vivek Sivaraman Narayanaswamy; Jayaraman J. Thiagarajan; Andreas Spanias (Interspeech, 2021)

Designing Counterfactual Generators using Deep Model Inversion. - Jayaraman J. Thiagarajan; Vivek Sivaraman Narayanaswamy; Deepta Rajan; Jason Liang; Akshay Chaudhari; Andreas Spanias (NeurIPS, 2021)

Loss Estimators Improve Model Generalization. - Vivek Sivaraman Narayanaswamy; Jayaraman J. Thiagarajan; Deepta Rajan; Andreas Spanias (CoRR, 2021)

COVID-19 detection using cough sound analysis and deep learning algorithms. - Sunil Rao; Vivek Sivaraman Narayanaswamy; Michael Esposito; Jayaraman J. Thiagarajan; Andreas Spanias (Intell. Decis. Technol., 2021)

Predicting the Generalization Gap in Deep Models using Anchoring. - Vivek Sivaraman Narayanaswamy; Rushil Anirudh; Irene Kim; Yamen Mubarka; Andreas Spanias; Jayaraman J. Thiagarajan (ICASSP, 2022)

Improved StyleGAN-v2 based Inversion for Out-of-Distribution Images. - Rakshith Subramanyam; Vivek Sivaraman Narayanaswamy; Mark Naufel; Andreas Spanias; Jayaraman J. Thiagarajan (ICML, 2022)

The ASU-DCU International Research and Workforce Development Program on Sensors and Machine Learning. - 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 (IISA, 2022)

Quantum Machine Learning for Photovoltaic Topology Optimization. - Glen S. Uehara; Vivek Sivaraman Narayanaswamy; Cihan Tepedelenlioglu; Andreas Spanias (IISA, 2022)

Single Model Uncertainty Estimation via Stochastic Data Centering. - Jayaraman J. Thiagarajan; Rushil Anirudh; Vivek Sivaraman Narayanaswamy; Timo Bremer (NeurIPS, 2022)

Revisiting Inlier and Outlier Specification for Improved Out-of-Distribution Detection. - Vivek Sivaraman Narayanaswamy; Yamen Mubarka; Rushil Anirudh; Deepta Rajan; Andreas Spanias; Jayaraman J. Thiagarajan (CoRR, 2022)

Instruction Tools for Signal Processing and Machine Learning for Ion-Channel Sensors. - 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; et al. (Int. J. Virtual Pers. Learn. Environ., 2022)

Signal Analysis-Synthesis Using the Quantum Fourier Transform. - Aradhita Sharma; Glen S. Uehara; Vivek Sivaraman Narayanaswamy; Leslie Miller; Andreas Spanias (ICASSP, 2023)

Exploring Inlier and Outlier Specification for Improved Medical OOD Detection. - Vivek Sivaraman Narayanaswamy; Yamen Mubarka; Rushil Anirudh; Deepta Rajan; Jayaraman J. Thiagarajan (ICCV (Workshops), 2023)

AN L2-Normalized Spatial Attention Network for Accurate and Fast Classification of Brain Tumors in 2D T1-Weighted CE-MRI Images. - Grace Billingsley; Julia Dietlmeier; Vivek Sivaraman Narayanaswamy; Andreas Spanias; Noel E. O'Connor (ICIP, 2023)

Know Your Space: Inlier and Outlier Construction for Calibrating Medical OOD Detectors. - Vivek Sivaraman Narayanaswamy; Yamen Mubarka; Rushil Anirudh; Deepta Rajan; Andreas Spanias; Jayaraman J. Thiagarajan (MIDL, 2023)

Optimizing Solar Power Using Array Topology Reconfiguration With Regularized Deep Neural Networks. - Vivek Sivaraman Narayanaswamy; Raja Ayyanar 001; Cihan Tepedelenlioglu; Devarajan Srinivasan; Andreas Spanias (IEEE Access, 2023)

PAGER: A Framework for Failure Analysis of Deep Regression Models. - Jayaraman J. Thiagarajan; Vivek Sivaraman Narayanaswamy; Puja Trivedi; Rushil Anirudh (CoRR, 2023)

DECIDER: Leveraging Foundation Model Priors for Improved Model Failure Detection and Explanation. - Rakshith Subramanyam; Kowshik Thopalli; Vivek Sivaraman Narayanaswamy; Jayaraman J. Thiagarajan (ECCV (79), 2024)

The Double-Edged Sword Of Ai Safety: Balancing Anomaly Detection and OOD Generalization Via Model Anchoring. - Vivek Sivaraman Narayanaswamy; Rushil Anirudh; Jayaraman J. Thiagarajan (ICASSP, 2024)

PAGER: Accurate Failure Characterization in Deep Regression Models. - Jayaraman J. Thiagarajan; Vivek Sivaraman Narayanaswamy; Puja Trivedi; Rushil Anirudh (ICML, 2024)

On the Use of Anchoring for Training Vision Models. - Vivek Sivaraman Narayanaswamy; Kowshik Thopalli; Rushil Anirudh; Yamen Mubarka; Wesam Sakla; Jayaraman J. Thiagarajan (NeurIPS, 2024)

The Surprising Utility of Group Partitioning in Improving Conformal Prediction of Visual Classifiers under Distributional Shifts. - Kowshik Thopalli; Vivek Sivaraman Narayanaswamy; Jayaraman J. Thiagarajan (CVPR Workshops, 2025)

Leveraging Registers in Vision Transformers for Robust Adaptation. - Srikar Yellapragada; Kowshik Thopalli; Vivek Sivaraman Narayanaswamy; Wesam Sakla; Yang Liu; Yamen Mubarka; Dimitris Samaras; Jayaraman J. Thiagarajan (ICASSP, 2025)