Rushil Anirudh

116 papers A* 11A 10B 2C 2Misc 11Journal 66Unranked 12

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Multitask deep learning for the emulation and calibration of an agent-based malaria transmission model. PLoS Comput. Biol. Agastya Mondal, Rushil Anirudh, Prashanth Selvaraj
2024	—	`conf`	'Eyes of a Hawk and Ears of a Fox': Part Prototype Network for Generalized Zero-Shot Learning. CVPR Workshops Joshua Feinglass, Jayaraman J. Thiagarajan, Rushil Anirudh, T. S. Jayram, Yezhou Yang
2024	J	`jnl`	'Eyes of a Hawk and Ears of a Fox': Part Prototype Network for Generalized Zero-Shot Learning. CoRR Joshua Feinglass, Jayaraman J. Thiagarajan, Rushil Anirudh, T. S. Jayram, Yezhou Yang
2024	A*	`conf`	Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks. ICLR Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan
2024	J	`jnl`	Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks. CoRR Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan
2024	Misc	`conf`	Exploring the Utility of Clip Priors for Visual Relationship Prediction. ICASSP Rakshith Subramanyam, T. S. Jayram, Rushil Anirudh, 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
2024	J	`jnl`	Transformer-powered surrogates close the ICF simulation-experiment gap with extremely limited data. Mach. Learn. Sci. Technol. Matthew L. Olson, Shusen Liu, Jayaraman J. Thiagarajan, Bogdan Kustowski, Weng-Keen Wong, Rushil Anirudh
2023	J	`jnl`	Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks. CoRR Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan
2023	J	`jnl`	CREPE: Learnable Prompting With CLIP Improves Visual Relationship Prediction. CoRR Rakshith Subramanyam, T. S. Jayram, Rushil Anirudh, Jayaraman J. Thiagarajan
2023	A	`conf`	Contrastive Knowledge-Augmented Meta-Learning for Few-Shot Classification. WACV Rakshith Subramanyam, Mark Heimann, T. S. Jayram, Rushil Anirudh, Jayaraman J. Thiagarajan
2023	A*	`conf`	Cross-GAN Auditing: Unsupervised Identification of Attribute Level Similarities and Differences Between Pretrained Generative Models. CVPR Matthew L. Olson, Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Weng-Keen Wong
2023	J	`jnl`	Cross-GAN Auditing: Unsupervised Identification of Attribute Level Similarities and Differences between Pretrained Generative Models. CoRR Matthew L. Olson, Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Weng-Keen Wong
2023	A*	`conf`	DOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstruction. ICCV Jiaming Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Stewart He, K. Aditya Mohan, Ulugbek S. Kamilov, Hyojin Kim
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	A	`conf`	Improving Diversity with Adversarially Learned Transformations for Domain Generalization. WACV Tejas Gokhale, Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Chitta Baral, Yezhou Yang
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`	PAGER: A Framework for Failure Analysis of Deep Regression Models. CoRR Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Puja Trivedi, Rushil Anirudh
2023	Misc	`conf`	Robust Time Series Recovery and Classification Using Test-Time Noise Simulator Networks. ICASSP Eun Som Jeon, Suhas Lohit, Rushil Anirudh, Pavan K. Turaga
2023	J	`jnl`	The Surprising Effectiveness of Deep Orthogonal Procrustes Alignment in Unsupervised Domain Adaptation. IEEE Access Kowshik Thopalli, Rushil Anirudh, Pavan K. Turaga, Jayaraman J. Thiagarajan
2023	J	`jnl`	Transformer-Powered Surrogates Close the ICF Simulation-Experiment Gap with Extremely Limited Data. CoRR Matthew L. Olson, Shusen Liu, Jayaraman J. Thiagarajan, Bogdan Kustowski, Weng-Keen Wong, Rushil Anirudh
2022	J	`jnl`	A biology-informed similarity metric for simulated patches of human cell membrane. Mach. Learn. Sci. Technol. Harsh Bhatia, Jayaraman J. Thiagarajan, Rushil Anirudh, T. S. Jayram, Tomas Oppelstrup, Helgi I. Ingólfsson, Felice C. Lightstone, Peer-Timo Bremer
2022	—	`conf`	Accurate Calibration of Agent-based Epidemiological Models with Neural Network Surrogates. Healthcare AI and COVID-19 Workshop Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Timothy C. Germann, Sara Y. Del Valle, Frederick H. Streitz
2022	J	`jnl`	Contrastive Knowledge-Augmented Meta-Learning for Few-Shot Classification. CoRR Rakshith Subramanyam, Mark Heimann, Jayram S. Thathachar, Rushil Anirudh, Jayaraman J. Thiagarajan
2022	J	`jnl`	DOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstruction. CoRR Jiaming Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Stewart He, K. Aditya Mohan, Ulugbek S. Kamilov, Hyojin Kim
2022	J	`jnl`	Enabling machine learning-ready HPC ensembles with Merlin. Future Gener. Comput. Syst. J. Luc Peterson, Benjamin Bay, Joe Koning, Peter B. Robinson, Jessica Semler, Jeremy White, Rushil Anirudh, Kevin Athey, Peer-Timo Bremer, Francesco Di Natale, David Fox, Jim A. Gaffney, Sam Ade Jacobs, Bhavya Kailkhura, Bogdan Kustowski, Steve H. Langer, Brian K. Spears, Jayaraman J. Thiagarajan, Brian Van Essen, Jae-Seung Yeom
2022	J	`jnl`	Improving Diversity with Adversarially Learned Transformations for Domain Generalization. CoRR Tejas Gokhale, Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Chitta Baral, Yezhou Yang
2022	—	`conf`	Intracardiac Electrical Imaging Using the 12-Lead ECG: A Machine Learning Approach Using Synthetic Data. CinC Mikel Landajuela, Rushil Anirudh, Joe Loscazo, Robert Blake
2022	—	`conf`	Machine Learning-Powered Mitigation Policy Optimization in Epidemiological Models. Healthcare AI and COVID-19 Workshop Jayaraman J. Thiagarajan, Rushil Anirudh, Peer-Timo Bremer, Timothy C. Germann, Sara Y. Del Valle, Frederick H. Streitz
2022	J	`jnl`	On-the-fly Object Detection using StyleGAN with CLIP Guidance. CoRR Yuzhe Lu, Shusen Liu, Jayaraman J. Thiagarajan, Wesam A. Sakla, Rushil Anirudh
2022	C	`conf`	Out of Distribution Detection via Neural Network Anchoring. ACML Rushil Anirudh, Jayaraman J. Thiagarajan
2022	J	`jnl`	Out of Distribution Detection via Neural Network Anchoring. CoRR Rushil Anirudh, Jayaraman J. Thiagarajan
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	J	`jnl`	Revisiting Deep Subspace Alignment for Unsupervised Domain Adaptation. CoRR Kowshik Thopalli, Jayaraman J. Thiagarajan, Rushil Anirudh, Pavan K. Turaga
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	Misc	`conf`	Sparsity Improves Unsupervised Attribute Discovery in Stylegan. ICASSP Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer
2022	J	`jnl`	Suppressing simulation bias in multi-modal data using transfer learning. Mach. Learn. Sci. Technol. Bogdan Kustowski, Jim A. Gaffney, Brian K. Spears, Gemma J. Anderson, Rushil Anirudh, Peer-Timo Bremer, Jayaraman J. Thiagarajan, Michael K. G. Kruse, Ryan Nora
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	A*	`conf`	Attribute-Guided Adversarial Training for Robustness to Natural Perturbations. AAAI Tejas Gokhale, Rushil Anirudh, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Chitta Baral, Yezhou Yang
2021	—	`conf`	Data-Driven Estimation of Temporal-Sampling Errors in Unsteady Flows. ISVC (1) Harsh Bhatia, Steve Petruzza, Rushil Anirudh, Attila Gyulassy, Robert M. Kirby, Valerio Pascucci, Peer-Timo Bremer
2021	A*	`conf`	Dynamic CT Reconstruction from Limited Views with Implicit Neural Representations and Parametric Motion Fields. ICCV Albert W. Reed, Hyojin Kim, Rushil Anirudh, K. Aditya Mohan, Kyle Champley, Jingu Kang, Suren Jayasuriya
2021	A	`conf`	Generative Patch Priors for Practical Compressive Image Recovery. WACV Rushil Anirudh, Suhas Lohit, Pavan K. Turaga
2021	J	`jnl`	Geometric Priors for Scientific Generative Models in Inertial Confinement Fusion. CoRR Ankita Shukla, Rushil Anirudh, Eugene Kur, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Brian K. Spears, Tammy Ma, Pavan K. Turaga
2021	J	`jnl`	MARGIN: Uncovering Deep Neural Networks Using Graph Signal Analysis. Frontiers Big Data Rushil Anirudh, Jayaraman J. Thiagarajan, Rahul Sridhar, Peer-Timo Bremer
2021	J	`jnl`	MR-GAN: Manifold Regularized Generative Adversarial Networks for Scientific Data. SIAM J. Math. Data Sci. Qunwei Li, Bhavya Kailkhura, Rushil Anirudh, Jize Zhang, Yi Zhou, Yingbin Liang, Thomas Yong-Jin Han, Pramod K. Varshney
2021	A	`conf`	Recovering Trajectories of Unmarked Joints in 3D Human Actions Using Latent Space Optimization. WACV Suhas Lohit, Rushil Anirudh, Pavan K. Turaga
2021	J	`jnl`	Transfer learning suppresses simulation bias in predictive models built from sparse, multi-modal data. CoRR Bogdan Kustowski, Jim A. Gaffney, Brian K. Spears, Gemma J. Anderson, Rushil Anirudh, Peer-Timo Bremer, Jayaraman J. Thiagarajan
2021	J	`jnl`	Δ-UQ: Accurate Uncertainty Quantification via Anchor Marginalization. CoRR Rushil Anirudh, Jayaraman J. Thiagarajan
2020	J	`jnl`	Accurate Calibration of Agent-based Epidemiological Models with Neural Network Surrogates. CoRR Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Timothy C. Germann, Sara Y. Del Valle, Frederick H. Streitz
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	J	`jnl`	Attribute-Guided Adversarial Training for Robustness to Natural Perturbations. CoRR Tejas Gokhale, Rushil Anirudh, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Chitta Baral, Yezhou Yang
2020	J	`jnl`	Designing Accurate Emulators for Scientific Processes using Calibration-Driven Deep Models. CoRR Jayaraman J. Thiagarajan, Bindya Venkatesh, Rushil Anirudh, Peer-Timo Bremer, Jim Gaffney, Gemma Anderson, Brian K. Spears
2020	J	`jnl`	Generative Patch Priors for Practical Compressive Image Recovery. CoRR Rushil Anirudh, Suhas Lohit, Pavan K. Turaga
2020	J	`jnl`	Improved surrogates in inertial confinement fusion with manifold and cycle consistencies. Proc. Natl. Acad. Sci. USA Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Brian K. Spears
2020	J	`jnl`	Machine Learning-Powered Mitigation Policy Optimization in Epidemiological Models. CoRR Jayaraman J. Thiagarajan, Peer-Timo Bremer, Rushil Anirudh, Timothy C. Germann, Sara Y. Del Valle, Frederick H. Streitz
2020	J	`jnl`	Meaningful uncertainties from deep neural network surrogates of large-scale numerical simulations. CoRR Gemma J. Anderson, Jim A. Gaffney, Brian K. Spears, Peer-Timo Bremer, Rushil Anirudh, Jayaraman J. Thiagarajan
2020	J	`jnl`	MimicGAN: Robust Projection onto Image Manifolds with Corruption Mimicking. Int. J. Comput. Vis. Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Peer-Timo Bremer
2020	Misc	`conf`	Rate-Invariant Autoencoding of Time-Series. ICASSP Kaushik Koneripalli, Suhas Lohit, Rushil Anirudh, Pavan K. Turaga
2020	J	`jnl`	Recovering Trajectories of Unmarked Joints in 3D Human Actions Using Latent Space Optimization. CoRR Suhas Lohit, Rushil Anirudh, Pavan K. Turaga
2020	J	`jnl`	Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications. IEEE Trans. Vis. Comput. Graph. Shusen Liu, Jim Gaffney, J. Luc Peterson, Peter B. Robinson, Harsh Bhatia, Valerio Pascucci, Brian K. Spears, Peer-Timo Bremer, Di Wang, Dan Maljovec, Rushil Anirudh, Jayaraman J. Thiagarajan, Sam Ade Jacobs, Brian C. Van Essen, David Hysom, Jae-Seung Yeom
2020	A	`conf`	The Case of Performance Variability on Dragonfly-based Systems. IPDPS Abhinav Bhatele, Jayaraman J. Thiagarajan, Taylor L. Groves, Rushil Anirudh, Staci A. Smith, Brandon Cook, David K. Lowenthal
2020	J	`jnl`	Uncovering interpretable relationships in high-dimensional scientific data through function preserving projections. Mach. Learn. Sci. Technol. Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer
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
2019	Misc	`conf`	Bootstrapping Graph Convolutional Neural Networks for Autism Spectrum Disorder Classification. ICASSP Rushil Anirudh, Jayaraman J. Thiagarajan
2019	J	`jnl`	Exploring Generative Physics Models with Scientific Priors in Inertial Confinement Fusion. CoRR Rushil Anirudh, Jayaraman J. Thiagarajan, Shusen Liu, Peer-Timo Bremer, Brian K. Spears
2019	J	`jnl`	Extreme Few-view CT Reconstruction using Deep Inference. CoRR Hyojin Kim, Rushil Anirudh, K. Aditya Mohan, Kyle Champley
2019	J	`jnl`	Function Preserving Projection for Scalable Exploration of High-Dimensional Data. CoRR Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer
2019	J	`jnl`	Improved Surrogates in Inertial Confinement Fusion with Manifold and Cycle Consistencies. CoRR Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Brian K. Spears
2019	J	`jnl`	Improving Limited Angle CT Reconstruction with a Robust GAN Prior. CoRR Rushil Anirudh, Hyojin Kim, Jayaraman J. Thiagarajan, K. Aditya Mohan, Kyle Champley
2019	J	`jnl`	Merlin: Enabling Machine Learning-Ready HPC Ensembles. CoRR J. Luc Peterson, Rushil Anirudh, Kevin Athey, Benjamin Bay, Peer-Timo Bremer, Vic Castillo, Francesco Di Natale, David Fox, Jim A. Gaffney, David Hysom, Sam Ade Jacobs, Bhavya Kailkhura, Joe Koning, Bogdan Kustowski, Steven H. Langer, Peter B. Robinson, Jessica Semler, Brian K. Spears, Jayaraman J. Thiagarajan, Brian Van Essen, Jae-Seung Yeom
2019	J	`jnl`	MimicGAN: Robust Projection onto Image Manifolds with Corruption Mimicking. CoRR Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Timo Bremer
2019	Misc	`conf`	Multiple Subspace Alignment Improves Domain Adaptation. ICASSP Kowshik Thopalli, Rushil Anirudh, Jayaraman J. Thiagarajan, Pavan K. Turaga
2019	C	`conf`	Parallelizing Training of Deep Generative Models on Massive Scientific Datasets. CLUSTER 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	J	`jnl`	Parallelizing Training of Deep Generative Models on Massive Scientific Datasets. CoRR Sam Ade Jacobs, Brian Van Essen, David Hysom, Jae-Seung Yeom, Tim Moon, Rushil Anirudh, Jayaraman J. Thiagarajan, Shusen Liu, Peer-Timo Bremer, Jim Gaffney, Tom Benson, Peter B. Robinson, J. Luc Peterson, Brian K. Spears
2019	J	`jnl`	SALT: Subspace Alignment as an Auxiliary Learning Task for Domain Adaptation. CoRR Kowshik Thopalli, Jayaraman J. Thiagarajan, Rushil Anirudh, Pavan K. Turaga
2019	J	`jnl`	Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications. CoRR Shusen Liu, Di Wang, Dan Maljovec, Rushil Anirudh, Jayaraman J. Thiagarajan, Sam Ade Jacobs, Brian C. Van Essen, David Hysom, Jae-Seung Yeom, Jim Gaffney, J. Luc Peterson, Peter B. Robinson, Harsh Bhatia, Valerio Pascucci, Brian K. Spears, Peer-Timo Bremer
2019	Misc	`conf`	Understanding Deep Neural Networks through Input Uncertainties. ICASSP Jayaraman J. Thiagarajan, Irene Kim, Rushil Anirudh, Peer-Timo Bremer
2019	Misc	`conf`	Unsupervised Dimension Selection Using a Blue Noise Graph Spectrum. ICASSP Jayaraman J. Thiagarajan, Rushil Anirudh, Rahul Sridhar, Peer-Timo Bremer
2018	J	`jnl`	An Unsupervised Approach to Solving Inverse Problems using Generative Adversarial Networks. CoRR Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Timo Bremer
2018	A	`conf`	Bootstrapping Parameter Space Exploration for Fast Tuning. ICS Jayaraman J. Thiagarajan, Nikhil Jain, Rushil Anirudh, Alfredo Giménez, Rahul Sridhar, Aniruddha Marathe, Tao Wang, Murali Emani, Abhinav Bhatele, Todd Gamblin
2018	A*	`conf`	Lose the Views: Limited Angle CT Reconstruction via Implicit Sinogram Completion. CVPR Rushil Anirudh, Hyojin Kim, Jayaraman J. Thiagarajan, K. Aditya Mohan, Kyle Champley, Timo Bremer
2018	J	`jnl`	MR-GAN: Manifold Regularized Generative Adversarial Networks. CoRR Qunwei Li, Bhavya Kailkhura, Rushil Anirudh, Yi Zhou, Yingbin Liang, Pramod K. Varshney
2018	J	`jnl`	MimicGAN: Corruption-Mimicking for Blind Image Recovery & Adversarial Defense. CoRR Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Timo Bremer
2018	J	`jnl`	Multiple Subspace Alignment Improves Domain Adaptation. CoRR Kowshik Thopalli, Rushil Anirudh, Jayaraman J. Thiagarajan, Pavan K. Turaga
2018	A	`conf`	PADDLE: Performance Analysis Using a Data-Driven Learning Environment. IPDPS Jayaraman J. Thiagarajan, Rushil Anirudh, Bhavya Kailkhura, Nikhil Jain, Tanzima Z. Islam, Abhinav Bhatele, Jae-Seung Yeom, Todd Gamblin
2018	J	`jnl`	Understanding Deep Neural Networks through Input Uncertainties. CoRR Jayaraman J. Thiagarajan, Irene Kim, Rushil Anirudh, Peer-Timo Bremer
2018	J	`jnl`	Unsupervised Dimension Selection using a Blue Noise Spectrum. CoRR Jayaraman J. Thiagarajan, Rushil Anirudh, Rahul Sridhar, Peer-Timo Bremer
2017	J	`jnl`	Bootstrapping Graph Convolutional Neural Networks for Autism Spectrum Disorder Classification. CoRR Rushil Anirudh, Jayaraman J. Thiagarajan
2017	J	`jnl`	Elastic Functional Coding of Riemannian Trajectories. IEEE Trans. Pattern Anal. Mach. Intell. Rushil Anirudh, Pavan K. Turaga, Jingyong Su, Anuj Srivastava
2017	J	`jnl`	Influential Sample Selection: A Graph Signal Processing Approach. CoRR Rushil Anirudh, Jayaraman J. Thiagarajan, Rahul Sridhar, Timo Bremer
2017	J	`jnl`	Lose The Views: Limited Angle CT Reconstruction via Implicit Sinogram Completion. CoRR Rushil Anirudh, Hyojin Kim, Jayaraman J. Thiagarajan, K. Aditya Mohan, Kyle Champley, Peer-Timo Bremer
2017	—	`ch.`	Optimization Problems Associated with Manifold-Valued Curves with Applications in Computer Vision. Handbook of Convex Optimization Methods in Imaging Science Rushil Anirudh, Pavan K. Turaga, Anuj Srivastava
2017	A	`conf`	Performance modeling under resource constraints using deep transfer learning. SC Aniruddha Marathe, Rushil Anirudh, Nikhil Jain, Abhinav Bhatele, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Jae-Seung Yeom, Barry Rountree, Todd Gamblin
2017	—	`conf`	Poisson Disk Sampling on the Grassmannnian: Applications in Subspace Optimization. CVPR Workshops Rushil Anirudh, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Peer-Timo Bremer
2016	—	`conf`	A Riemannian Framework for Statistical Analysis of Topological Persistence Diagrams. CVPR Workshops Rushil Anirudh, Vinay Venkataraman, Karthikeyan Natesan Ramamurthy, Pavan K. Turaga
2016	J	`jnl`	A Riemannian Framework for Statistical Analysis of Topological Persistence Diagrams. CoRR Rushil Anirudh, Vinay Venkataraman, Karthikeyan Natesan Ramamurthy, Pavan K. Turaga
2016	J	`jnl`	Diversity Promoting Online Sampling for Streaming Video Summarization. CoRR Rushil Anirudh, Ahnaf Masroor, Pavan K. Turaga
2016	B	`conf`	Diversity promoting online sampling for streaming video summarization. ICIP Rushil Anirudh, Ahnaf Masroor, Pavan K. Turaga
2016	J	`jnl`	Elastic Functional Coding of Riemannian Trajectories. CoRR Rushil Anirudh, Pavan K. Turaga, Jingyong Su, Anuj Srivastava
2016	J	`jnl`	Geometry-Based Symbolic Approximation for Fast Sequence Matching on Manifolds. Int. J. Comput. Vis. Rushil Anirudh, Pavan K. Turaga
2016	—	`conf`	Lung nodule detection using 3D convolutional neural networks trained on weakly labeled data. Computer-Aided Diagnosis Rushil Anirudh, Jayaraman J. Thiagarajan, Timo Bremer, Hyojin Kim
2016	—	`conf`	Riemannian Geometric Approaches for Measuring Movement Quality. CVPR Workshops Anirudh Som, Rushil Anirudh, Qiao Wang, Pavan K. Turaga
2016	—	`—`	Statistical and Dynamical Modeling of Riemannian Trajectories with Application to Human Movement Analysis. Rushil Anirudh
2015	A*	`conf`	Elastic functional coding of human actions: From vector-fields to latent variables. CVPR Rushil Anirudh, Pavan K. Turaga, Jingyong Su, Anuj Srivastava
2015	B	`conf`	Geometric Compression of Orientation Signals for Fast Gesture Analysis. DCC Aswin Sivakumar, Rushil Anirudh, Pavan K. Turaga
2015	—	`conf`	Towards realtime measurement of connectedness in human movement. MOCO Michael Krzyzaniak, Rushil Anirudh, Vinay Venkataraman, Pavan K. Turaga, Sha Xin Wei
2014	J	`jnl`	Geometry-based Adaptive Symbolic Approximation for Fast Sequence Matching on Manifolds: Applications to Activity Analysis. CoRR Rushil Anirudh, Pavan K. Turaga
2014	J	`jnl`	Interactively Test Driving an Object Detector: Estimating Performance on Unlabeled Data. CoRR Rushil Anirudh, Pavan K. Turaga
2014	A	`conf`	Interactively test driving an object detector: Estimating performance on unlabeled data. WACV Rushil Anirudh, Pavan K. Turaga
2013	Misc	`conf`	A heterogeneous dictionary model for representation and recognition of human actions. ICASSP Rushil Anirudh, Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Pavan K. Turaga, Andreas Spanias