Thiagarajan, Jayaraman J.

32 publications

CVPRW 2025 The Surprising Utility of Group Partitioning in Improving Conformal Prediction of Visual Classifiers Under Distributional Shifts Kowshik Thopalli, Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan

CVPRW 2024 '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

ICLR 2024 Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan

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

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

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

ICLR 2023 A Closer Look at Model Adaptation Using Feature Distortion and Simplicity Bias Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan

ICMLW 2023 Adapting Blackbox Generative Models via Inversion Sinjini Mitra, Rakshith Subramanyam, Rushil Anirudh, Jayaraman J. Thiagarajan, Ankita Shukla, Pavan K. Turaga

WACV 2023 Contrastive Knowledge-Augmented Meta-Learning for Few-Shot Classification Rakshith Subramanyam, Mark Heimann, T.S. Jayram, Rushil Anirudh, Jayaraman J. Thiagarajan

CVPR 2023 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

ICCV 2023 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

NeurIPSW 2023 Estimating Epistemic Uncertainty of Graph Neural Networks Using Stochastic Centering Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan

ICCVW 2023 Exploring Inlier and Outlier Specification for Improved Medical OOD Detection Vivek Sivaraman Narayanaswamy, Yamen Mubarka, Rushil Anirudh, Deepta Rajan, Jayaraman J. Thiagarajan

WACV 2023 Improving Diversity with Adversarially Learned Transformations for Domain Generalization Tejas Gokhale, Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Chitta Baral, Yezhou Yang

ICCVW 2023 InterAug: A Tuning-Free Augmentation Policy for Data-Efficient and Robust Object Detection Kowshik Thopalli, Devi S, Jayaraman J. Thiagarajan

ICML 2023 Target-Aware Generative Augmentations for Single-Shot Adaptation Kowshik Thopalli, Rakshith Subramanyam, Pavan K. Turaga, Jayaraman J. Thiagarajan

NeurIPSW 2022 A Closer Look at Model Adaptation Using Feature Distortion and Simplicity Bias Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan

ACML 2022 Domain Alignment Meets Fully Test-Time Adaptation Kowshik Thopalli, Pavan Turaga, Jayaraman J Thiagarajan

ICML 2022 Improved StyleGAN-V2 Based Inversion for Out-of-Distribution Images Rakshith Subramanyam, Vivek Narayanaswamy, Mark Naufel, Andreas Spanias, Jayaraman J. Thiagarajan

ACML 2022 Out of Distribution Detection via Neural Network Anchoring Rushil Anirudh, Jayaraman J. Thiagarajan

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

AAAI 2021 Attribute-Guided Adversarial Training for Robustness to Natural Perturbations Tejas Gokhale, Rushil Anirudh, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Chitta Baral, Yezhou Yang

NeurIPSW 2021 Multi-Domain Ensembles for Domain Generalization Kowshik Thopalli, Sameeksha Katoch, Jayaraman J. Thiagarajan, Pavan K. Turaga, Andreas Spanias

NeurIPSW 2021 Re-Labeling Domains Improves Multi-Domain Generalization Kowshik Thopalli, Pavan K. Turaga, Jayaraman J. Thiagarajan

AAAI 2021 Uncertainty-Matching Graph Neural Networks to Defend Against Poisoning Attacks Uday Shankar Shanthamallu, Jayaraman J. Thiagarajan, Andreas Spanias

NeurIPSW 2021 Unsupervised Attribute Alignment for Characterizing Distribution Shift Matthew Lyle Olson, Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Weng-Keen Wong, Peer-timo Bremer

AAAI 2020 Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors Jayaraman J. Thiagarajan, Bindya Venkatesh, Prasanna Sattigeri, Peer-Timo Bremer

NeurIPSW 2019 Improving Limited Angle CT Reconstruction with a Robust GAN Prior Rushil Anirudh, Hyojin Kim, Jayaraman J. Thiagarajan, K. Aditya Mohan, Kyle Champley

JMLR 2018 A Spectral Approach for the Design of Experiments: Design, Analysis and Algorithms Bhavya Kailkhura, Jayaraman J. Thiagarajan, Charvi Rastogi, Pramod K. Varshney, Peer-Timo Bremer

AAAI 2018 Attend and Diagnose: Clinical Time Series Analysis Using Attention Models Huan Song, Deepta Rajan, Jayaraman J. Thiagarajan, Andreas Spanias

ICCVW 2017 Learning Robust Representations for Computer Vision Peng Zheng, Aleksandr Y. Aravkin, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy

CVPRW 2017 Poisson Disk Sampling on the Grassmannnian: Applications in Subspace Optimization Rushil Anirudh, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Peer-Timo Bremer