Jayaraman J. Thiagarajan
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
84
Venues
25
Active years
2008–2025
Best venue rank
A*
Where they publish
- MulticonferenceICASSP26 papers
- BICIP6 papers
- A*CVPR5 papers
- A*ICML5 papers
- A*AAAI5 papers
- NationalACSSC5 papers
- ASC5 papers
- AInterspeech3 papers
- CFIE3 papers
- A*ICLR2 papers
- A*ICCV2 papers
- AWACV2 papers
- CACML2 papers
- NationalSGAI2 papers
- AHPDC1 paper
- ASDM1 paper
- A*ECCV1 paper
- BCOMPSAC1 paper
- BISPASS1 paper
- AMICCAI1 paper
- CCLUSTER1 paper
- CICMLA1 paper
- AICS1 paper
- A*ICDM1 paper
- CBIBE1 paper
Papers
84 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | CVPR | The Surprising Utility of Group Partitioning in Improving Conformal Prediction of Visual Classifiers under Distributional Shifts. | Kowshik Thopalli, Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan |
| 2025 | HPDC | ModelX : A Novel Transfer Learning Approach Across Heterogeneous Datasets. | Arunavo Dey, Neil Antony, Aakash Raj Dhakal, Kowshik Thopalli, Jayaraman J. Thiagarajan, Tapasya Patki, Aniruddha Marathe, Tom Scogland, Jae-Seung Yeom, Tanzima Z. Islam |
| 2025 | ICASSP | On The Role of Prompt Construction In Enhancing Efficacy and Efficiency of LLM-Based Tabular Data Generation. | Banooqa H. Banday, Kowshik Thopalli, Tanzima Z. Islam, Jayaraman J. Thiagarajan |
| 2025 | ICASSP | Leveraging Registers in Vision Transformers for Robust Adaptation. | Srikar Yellapragada, Kowshik Thopalli, Vivek Sivaraman Narayanaswamy, Wesam A. Sakla, Yang Liu, Yamen Mubarka, Dimitris Samaras, Jayaraman J. Thiagarajan |
| 2025 | SDM | Conformal Edge-Weight Prediction in Latent Space. | Akash Choudhuri, Yongjian Zhong, Mehrdad Moharrami, Christine Klymko, Mark Heimann, Jayaraman J. Thiagarajan, Bijaya Adhikari |
| 2024 | CVPR | 'Eyes of a Hawk and Ears of a Fox': Part Prototype Network for Generalized Zero-Shot Learning. | Joshua Feinglass, Jayaraman J. Thiagarajan, Rushil Anirudh, T. S. Jayram, Yezhou Yang |
| 2024 | ECCV | DECIDER: Leveraging Foundation Model Priors for Improved Model Failure Detection and Explanation. | Rakshith Subramanyam, Kowshik Thopalli, Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan |
| 2024 | ICASSP | The Double-Edged Sword Of Ai Safety: Balancing Anomaly Detection and OOD Generalization Via Model Anchoring. | Vivek Sivaraman Narayanaswamy, Rushil Anirudh, Jayaraman J. Thiagarajan |
| 2024 | ICASSP | Exploring the Utility of Clip Priors for Visual Relationship Prediction. | Rakshith Subramanyam, T. S. Jayram, Rushil Anirudh, Jayaraman J. Thiagarajan |
| 2024 | ICASSP | On Estimating Link Prediction Uncertainty Using Stochastic Centering. | Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan |
| 2024 | ICLR | Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks. | Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan |
| 2024 | ICML | PAGER: Accurate Failure Characterization in Deep Regression Models. | Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Puja Trivedi, Rushil Anirudh |
| 2023 | CVPR | Cross-GAN Auditing: Unsupervised Identification of Attribute Level Similarities and Differences Between Pretrained Generative Models. | Matthew L. Olson, Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Weng-Keen Wong |
| 2023 | ICASSP | Single-Shot Domain Adaptation via Target-Aware Generative Augmentations. | Rakshith Subramanyam, Kowshik Thopalli, Spring Berman, Pavan K. Turaga, Jayaraman J. Thiagarajan |
| 2023 | ICASSP | A Closer Look At Scoring Functions And Generalization Prediction. | Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan |
| 2023 | ICCV | DOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstruction. | Jiaming Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Stewart He, K. Aditya Mohan, Ulugbek S. Kamilov, Hyojin Kim |
| 2023 | ICLR | A Closer Look at Model Adaptation using Feature Distortion and Simplicity Bias. | Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan |
| 2023 | ICML | Target-Aware Generative Augmentations for Single-Shot Adaptation. | Kowshik Thopalli, Rakshith Subramanyam, Pavan K. Turaga, Jayaraman J. Thiagarajan |
| 2023 | WACV | Improving Diversity with Adversarially Learned Transformations for Domain Generalization. | Tejas Gokhale, Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Chitta Baral, Yezhou Yang |
| 2023 | WACV | Contrastive Knowledge-Augmented Meta-Learning for Few-Shot Classification. | Rakshith Subramanyam, Mark Heimann, T. S. Jayram, Rushil Anirudh, Jayaraman J. Thiagarajan |
| 2022 | ACML | Out of Distribution Detection via Neural Network Anchoring. | Rushil Anirudh, Jayaraman J. Thiagarajan |
| 2022 | ACML | Domain Alignment Meets Fully Test-Time Adaptation. | Kowshik Thopalli, Pavan K. Turaga, Jayaraman J. Thiagarajan |
| 2022 | ICASSP | Sparsity Improves Unsupervised Attribute Discovery in Stylegan. | Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer |
| 2022 | ICASSP | Predicting the Generalization Gap in Deep Models using Anchoring. | Vivek Sivaraman Narayanaswamy, Rushil Anirudh, Irene Kim, Yamen Mubarka, Andreas Spanias, Jayaraman J. Thiagarajan |
| 2022 | ICML | Accurate Calibration of Agent-based Epidemiological Models with Neural Network Surrogates. | Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Timothy C. Germann, Sara Y. Del Valle, Frederick H. Streitz |
| 2022 | ICML | Improved StyleGAN-v2 based Inversion for Out-of-Distribution Images. | Rakshith Subramanyam, Vivek Sivaraman Narayanaswamy, Mark Naufel, Andreas Spanias, Jayaraman J. Thiagarajan |
| 2022 | ICML | Machine Learning-Powered Mitigation Policy Optimization in Epidemiological Models. | Jayaraman J. Thiagarajan, Rushil Anirudh, Peer-Timo Bremer, Timothy C. Germann, Sara Y. Del Valle, Frederick H. Streitz |
| 2021 | AAAI | Attribute-Guided Adversarial Training for Robustness to Natural Perturbations. | Tejas Gokhale, Rushil Anirudh, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Chitta Baral, Yezhou Yang |
| 2021 | AAAI | Uncertainty-Matching Graph Neural Networks to Defend Against Poisoning Attacks. | Uday Shankar Shanthamallu, Jayaraman J. Thiagarajan, Andreas Spanias |
| 2021 | AAAI | Accurate and Robust Feature Importance Estimation under Distribution Shifts. | Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Rushil Anirudh, Peer-Timo Bremer, Andreas Spanias |
| 2021 | COMPSAC | College Life is Hard! - Shedding Light on Stress Prediction for Autistic College Students using Data-Driven Analysis. | Tanzima Z. Islam, Philip Wu Liang, Forest Sweeney, Cody Pranger, Jayaraman J. Thiagarajan, Moushumi Sharmin, Shameem Ahmed |
| 2021 | ICASSP | Using Deep Image Priors to Generate Counterfactual Explanations. | Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Andreas Spanias |
| 2021 | Interspeech | On the Design of Deep Priors for Unsupervised Audio Restoration. | Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Andreas Spanias |
| 2021 | ISPASS | Comparative Code Structure Analysis using Deep Learning for Performance Prediction. | Tarek Ramadan, Tanzima Z. Islam, Chase Phelps, Nathan Pinnow, Jayaraman J. Thiagarajan |
| 2020 | AAAI | Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors. | Jayaraman J. Thiagarajan, Bindya Venkatesh, Prasanna Sattigeri, Peer-Timo Bremer |
| 2020 | ACSSC | Treeview and Disentangled Representations for Explaining Deep Neural Networks Decisions. | Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Bhavya Kailkhura |
| 2020 | ICASSP | A Regularized Attention Mechanism for Graph Attention Networks. | Uday Shankar Shanthamallu, Jayaraman J. Thiagarajan, Andreas Spanias |
| 2020 | ICASSP | Learn-By-Calibrating: Using Calibration As A Training Objective. | Jayaraman J. Thiagarajan, Bindya Venkatesh, Deepta Rajan |
| 2020 | Interspeech | Unsupervised Audio Source Separation Using Generative Priors. | Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Rushil Anirudh, Andreas Spanias |
| 2020 | MICCAI | Improving Reliability of Clinical Models Using Prediction Calibration. | Jayaraman J. Thiagarajan, Bindya Venkatesh, Deepta Rajan, Prasanna Sattigeri |
| 2019 | CLUSTER | Parallelizing Training of Deep Generative Models on Massive Scientific Datasets. | Sam Ade Jacobs, Jim Gaffney, Tom Benson, Peter B. Robinson, J. Luc Peterson, Brian K. Spears, Brian Van Essen, David Hysom, Jae-Seung Yeom, Tim Moon, Rushil Anirudh, Jayaraman J. Thiagarajan, Shusen Liu, Peer-Timo Bremer |
| 2019 | ICASSP | Bootstrapping Graph Convolutional Neural Networks for Autism Spectrum Disorder Classification. | Rushil Anirudh, Jayaraman J. Thiagarajan |
| 2019 | ICASSP | Designing an Effective Metric Learning Pipeline for Speaker Diarization. | Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Huan Song, Andreas Spanias |
| 2019 | ICASSP | Unsupervised Dimension Selection Using a Blue Noise Graph Spectrum. | Jayaraman J. Thiagarajan, Rushil Anirudh, Rahul Sridhar, Peer-Timo Bremer |
| 2019 | ICASSP | Understanding Deep Neural Networks through Input Uncertainties. | Jayaraman J. Thiagarajan, Irene Kim, Rushil Anirudh, Peer-Timo Bremer |
| 2019 | ICASSP | Multiple Subspace Alignment Improves Domain Adaptation. | Kowshik Thopalli, Rushil Anirudh, Jayaraman J. Thiagarajan, Pavan K. Turaga |
| 2019 | ICMLA | Distill-to-Label: Weakly Supervised Instance Labeling Using Knowledge Distillation. | Jayaraman J. Thiagarajan, Satyananda Kashyap, Alexandros Karargyris |
| 2019 | SC | Performance optimality or reproducibility: that is the question. | Tapasya Patki, Jayaraman J. Thiagarajan, Alexis Ayala, Tanzima Z. Islam |
| 2018 | AAAI | Attend and Diagnose: Clinical Time Series Analysis Using Attention Models. | Huan Song, Deepta Rajan, Jayaraman J. Thiagarajan, Andreas Spanias |
| 2018 | CVPR | Lose the Views: Limited Angle CT Reconstruction via Implicit Sinogram Completion. | Rushil Anirudh, Hyojin Kim, Jayaraman J. Thiagarajan, K. Aditya Mohan, Kyle Champley, Timo Bremer |
| 2018 | Interspeech | Triplet Network with Attention for Speaker Diarization. | Huan Song, Megan M. Willi, Jayaraman J. Thiagarajan, Visar Berisha, Andreas Spanias |
| 2018 | ICS | Bootstrapping Parameter Space Exploration for Fast Tuning. | Jayaraman J. Thiagarajan, Nikhil Jain, Rushil Anirudh, Alfredo Gimnez, Rahul Sridhar, Aniruddha Marathe, Tao Wang, Murali Emani, Abhinav Bhatele, Todd Gamblin |
| 2018 | SC | Mitigating inter-job interference using adaptive flow-aware routing. | Staci A. Smith, Clara E. Cromey, David K. Lowenthal, Jens Domke, Nikhil Jain, Jayaraman J. Thiagarajan, Abhinav Bhatele |
| 2017 | CVPR | Poisson Disk Sampling on the Grassmannnian: Applications in Subspace Optimization. | Rushil Anirudh, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Peer-Timo Bremer |
| 2017 | ICASSP | A deep learning approach to multiple kernel fusion. | Huan Song, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Andreas Spanias |
| 2017 | SC | Performance modeling under resource constraints using deep transfer learning. | Aniruddha Marathe, Rushil Anirudh, Nikhil Jain, Abhinav Bhatele, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Jae-Seung Yeom, Barry Rountree, Todd Gamblin |
| 2016 | ICASSP | Theoretical guarantees for poisson disk sampling using pair correlation function. | Bhavya Kailkhura, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Pramod K. Varshney |
| 2016 | ICASSP | Beyond L2-loss functions for learning sparse models. | Karthikeyan Natesan Ramamurthy, Aleksandr Y. Aravkin, Jayaraman J. Thiagarajan |
| 2016 | ICASSP | Consensus inference on mobile phone sensors for activity recognition. | Huan Song, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias, Pavan K. Turaga |
| 2016 | ICDM | Robust Local Scaling Using Conditional Quantiles of Graph Similarities. | Jayaraman J. Thiagarajan, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Bhavya Kailkhura |
| 2016 | ICIP | Auto-context modeling using multiple Kernel learning. | Huan Song, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias |
| 2016 | SC | A machine learning framework for performance coverage analysis of proxy applications. | Tanzima Z. Islam, Jayaraman J. Thiagarajan, Abhinav Bhatele, Martin Schulz, Todd Gamblin |
| 2016 | SC | Data-Driven Performance Modeling of Linear Solvers for Sparse Matrices. | Jae-Seung Yeom, Jayaraman J. Thiagarajan, Abhinav Bhatele, Greg Bronevetsky, Tzanio V. Kolev |
| 2015 | ICASSP | Subspace learning using consensus on the grassmannian manifold. | Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy |
| 2015 | ICCV | A Randomized Ensemble Approach to Industrial CT Segmentation. | Hyojin Kim, Jayaraman J. Thiagarajan, Peer-Timo Bremer |
| 2014 | ACSSC | Consensus inference with multilayer graphs for multi-modal data. | Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Rahul Sridhar, Premnishanth Kothandaraman, Ramanathan Nachiappan |
| 2014 | ACSSC | A scalable feature learning and tag prediction framework for natural environment sounds. | Prasanna Sattigeri, Jayaraman J. Thiagarajan, Mohit Shah, Karthikeyan Natesan Ramamurthy, Andreas Spanias |
| 2014 | ICASSP | Multiple kernel interpolation for inverting non-linear dimensionality reduction and dimension estimation. | Jayaraman J. Thiagarajan, Peer-Timo Bremer, Karthikeyan Natesan Ramamurthy |
| 2014 | ICIP | Image segmentation using consensus from hierarchical segmentation ensembles. | Hyojin Kim, Jayaraman J. Thiagarajan, Peer-Timo Bremer |
| 2014 | ICIP | Automatic image annotation using inverse maps from semantic embeddings. | Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Peer-Timo Bremer, Andreas Spanias |
| 2013 | ICASSP | A heterogeneous dictionary model for representation and recognition of human actions. | Rushil Anirudh, Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Pavan K. Turaga, Andreas Spanias |
| 2013 | ICASSP | Boosted dictionaries for image restoration based on sparse representations. | Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Andreas Spanias, Prasanna Sattigeri |
| 2012 | ACSSC | Learning dictionaries with graph embedding constraints. | Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Andreas Spanias |
| 2012 | BIBE | Automated tumor segmentation using kernel sparse representations. | Jayaraman J. Thiagarajan, Deepta Rajan, Karthikeyan Natesan Ramamurthy, David H. Frakes, Andreas Spanias |
| 2012 | FIE | Work in progress: Performing signal analysis laboratories using Android devices. | Suhas Ranganath, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Shuang Hu, Mahesh K. Banavar, Andreas Spanias |
| 2012 | ICASSP | Interactive DSP laboratories on mobile phones and tablets. | Jinru Liu, Shuang Hu, Jayaraman J. Thiagarajan, Xue Zhang, Suhas Ranganath, Mahesh K. Banavar, Andreas Spanias |
| 2012 | ICIP | Supervised local sparse coding of sub-image features for image retrieval. | Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Andreas Spanias |
| 2011 | ACSSC | Learning dictionaries for local sparse coding in image classification. | Jayaraman J. Thiagarajan, Andreas Spanias |
| 2011 | FIE | Work in progress - Interactive signal-processing labs and simulations on iOS devices. | Jinru Liu, Andreas Spanias, Mahesh K. Banavar, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Shuang Hu, Xue Zhang |
| 2011 | FIE | Work in progress - Modules and laboratories for a pathways course in signals and systems. | Kostas Tsakalis, Jayaraman J. Thiagarajan, Tolga M. Duman, Martin Reisslein, G. Tong Zhou, Xiaoli Ma, Photini Spanias |
| 2011 | ICIP | Improved sparse coding using manifold projections. | Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Andreas Spanias |
| 2009 | ICIP | Fast image registration with non-stationary Gauss-Markov random field templates. | Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Andreas Spanias |
| 2009 | SGAI | Template Learning using Wavelet Domain Statistical Models. | Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Andreas Spanias |
| 2008 | SGAI | Sparse Representations for Pattern Classification using Learned Dictionaries. | Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias |