Rushil Anirudh

ORCID

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 100

Top Venues

CoRR

ICASSP

WACV

Mach. Learn. Sci. Technol.

Arizona State University, Tempe, USA (PHD)

Education History

Arizona State University, Tempe, USA

PHD

Publications

Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan
Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks. CoRR (2024)
Jiaming Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Stewart He, K. Aditya Mohan, Ulugbek S. Kamilov, Hyojin Kim
DOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstruction. ICCV (2023)
Vivek Sivaraman Narayanaswamy, Yamen Mubarka, Rushil Anirudh, Deepta Rajan, Jayaraman J. Thiagarajan
Exploring Inlier and Outlier Specification for Improved Medical OOD Detection. ICCV (Workshops) (2023)
Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan
Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks. CoRR (2023)
Vivek Sivaraman Narayanaswamy, Yamen Mubarka, Rushil Anirudh, Deepta Rajan, Andreas Spanias, Jayaraman J. Thiagarajan
Know Your Space: Inlier and Outlier Construction for Calibrating Medical OOD Detectors. MIDL (2023)
Eun Som Jeon, Suhas Lohit, Rushil Anirudh, Pavan K. Turaga
Robust Time Series Recovery and Classification Using Test-Time Noise Simulator Networks. ICASSP (2023)
Rakshith Subramanyam, Mark Heimann, T. S. Jayram, Rushil Anirudh, Jayaraman J. Thiagarajan
Contrastive Knowledge-Augmented Meta-Learning for Few-Shot Classification. WACV (2023)
Tejas Gokhale, Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Chitta Baral, Yezhou Yang
Improving Diversity with Adversarially Learned Transformations for Domain Generalization. WACV (2023)
Matthew L. Olson, Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Weng-Keen Wong
Cross-GAN Auditing: Unsupervised Identification of Attribute Level Similarities and Differences Between Pretrained Generative Models. CVPR (2023)
Matthew L. Olson, Shusen Liu, Jayaraman J. Thiagarajan, Bogdan Kustowski, Weng-Keen Wong, Rushil Anirudh
Transformer-Powered Surrogates Close the ICF Simulation-Experiment Gap with Extremely Limited Data. CoRR (2023)
Rakshith Subramanyam, T. S. Jayram, Rushil Anirudh, Jayaraman J. Thiagarajan
CREPE: Learnable Prompting With CLIP Improves Visual Relationship Prediction. CoRR (2023)
Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Puja Trivedi, Rushil Anirudh
PAGER: A Framework for Failure Analysis of Deep Regression Models. CoRR (2023)
Matthew L. Olson, Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Weng-Keen Wong
Cross-GAN Auditing: Unsupervised Identification of Attribute Level Similarities and Differences between Pretrained Generative Models. CoRR (2023)
Kowshik Thopalli, Rushil Anirudh, Pavan K. Turaga, Jayaraman J. Thiagarajan
The Surprising Effectiveness of Deep Orthogonal Procrustes Alignment in Unsupervised Domain Adaptation. IEEE Access 11 (2023)
Vivek Sivaraman Narayanaswamy, Yamen Mubarka, Rushil Anirudh, Deepta Rajan, Andreas Spanias, Jayaraman J. Thiagarajan
Revisiting Inlier and Outlier Specification for Improved Out-of-Distribution Detection. CoRR (2022)
Rushil Anirudh, Jayaraman J. Thiagarajan
Out of Distribution Detection via Neural Network Anchoring. CoRR (2022)
Jayaraman J. Thiagarajan, Rushil Anirudh, Vivek Sivaraman Narayanaswamy, Peer-Timo Bremer
Single Model Uncertainty Estimation via Stochastic Data Centering. CoRR (2022)
Kowshik Thopalli, Jayaraman J. Thiagarajan, Rushil Anirudh, Pavan K. Turaga
Revisiting Deep Subspace Alignment for Unsupervised Domain Adaptation. CoRR (2022)
Vivek Sivaraman Narayanaswamy, Rushil Anirudh, Irene Kim, Yamen Mubarka, Andreas Spanias, Jayaraman J. Thiagarajan
Predicting the Generalization Gap in Deep Models using Anchoring. ICASSP (2022)
Yuzhe Lu, Shusen Liu, Jayaraman J. Thiagarajan, Wesam Sakla, Rushil Anirudh
On-the-fly Object Detection using StyleGAN with CLIP Guidance. CoRR (2022)
Jayaraman J. Thiagarajan, Rushil Anirudh, Peer-Timo Bremer, Timothy C. Germann, Sara Y. Del Valle, Frederick H. Streitz
Machine Learning-Powered Mitigation Policy Optimization in Epidemiological Models. Healthcare AI and COVID-19 Workshop (2022)
Rakshith Subramanyam, Mark Heimann, Jayram S. Thathachar, Rushil Anirudh, Jayaraman J. Thiagarajan
Contrastive Knowledge-Augmented Meta-Learning for Few-Shot Classification. CoRR (2022)
Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer
Sparsity Improves Unsupervised Attribute Discovery in Stylegan. ICASSP (2022)
Jiaming Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Stewart He, K. Aditya Mohan, Ulugbek S. Kamilov, Hyojin Kim
DOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstruction. CoRR (2022)
Harsh Bhatia, Jayaraman J. Thiagarajan, Rushil Anirudh, T. S. Jayram, Tomas Oppelstrup, Helgi I. Ingólfsson, Felice C. Lightstone, Peer-Timo Bremer
A biology-informed similarity metric for simulated patches of human cell membrane. Mach. Learn. Sci. Technol. 3 (3) (2022)
Jayaraman J. Thiagarajan, Rushil Anirudh, Vivek Sivaraman Narayanaswamy, Timo Bremer
Single Model Uncertainty Estimation via Stochastic Data Centering. NeurIPS (2022)
Tejas Gokhale, Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Chitta Baral, Yezhou Yang
Improving Diversity with Adversarially Learned Transformations for Domain Generalization. CoRR (2022)
Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Timothy C. Germann, Sara Y. Del Valle, Frederick H. Streitz
Accurate Calibration of Agent-based Epidemiological Models with Neural Network Surrogates. Healthcare AI and COVID-19 Workshop (2022)
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
Suppressing simulation bias in multi-modal data using transfer learning. Mach. Learn. Sci. Technol. 3 (1) (2022)
Rushil Anirudh, Jayaraman J. Thiagarajan
Out of Distribution Detection via Neural Network Anchoring. ACML (2022)
Mikel Landajuela, Rushil Anirudh, Joe Loscazo, Robert Blake
Intracardiac Electrical Imaging Using the 12-Lead ECG: A Machine Learning Approach Using Synthetic Data. CinC (2022)
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
Enabling machine learning-ready HPC ensembles with Merlin. Future Gener. Comput. Syst. 131 (2022)
Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Rushil Anirudh, Peer-Timo Bremer, Andreas Spanias
Accurate and Robust Feature Importance Estimation under Distribution Shifts. AAAI (2021)
Harsh Bhatia, Steve Petruzza, Rushil Anirudh, Attila Gyulassy, Robert M. Kirby, Valerio Pascucci, Peer-Timo Bremer
Data-Driven Estimation of Temporal-Sampling Errors in Unsteady Flows. ISVC (1) (2021)
Bogdan Kustowski, Jim A. Gaffney, Brian K. Spears, Gemma J. Anderson, Rushil Anirudh, Peer-Timo Bremer, Jayaraman J. Thiagarajan
Transfer learning suppresses simulation bias in predictive models built from sparse, multi-modal data. CoRR (2021)
Tejas Gokhale, Rushil Anirudh, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Chitta Baral, Yezhou Yang
Attribute-Guided Adversarial Training for Robustness to Natural Perturbations. AAAI (2021)
Qunwei Li, Bhavya Kailkhura, Rushil Anirudh, Jize Zhang, Yi Zhou, Yingbin Liang, Thomas Yong-Jin Han, Pramod K. Varshney
MR-GAN: Manifold Regularized Generative Adversarial Networks for Scientific Data. SIAM J. Math. Data Sci. 3 (4) (2021)
Rushil Anirudh, Jayaraman J. Thiagarajan
Δ-UQ: Accurate Uncertainty Quantification via Anchor Marginalization. CoRR (2021)
Albert W. Reed, Hyojin Kim, Rushil Anirudh, K. Aditya Mohan, Kyle Champley, Jingu Kang, Suren Jayasuriya
Dynamic CT Reconstruction from Limited Views with Implicit Neural Representations and Parametric Motion Fields. ICCV (2021)
Suhas Lohit, Rushil Anirudh, Pavan K. Turaga
Recovering Trajectories of Unmarked Joints in 3D Human Actions Using Latent Space Optimization. WACV (2021)
Rushil Anirudh, Jayaraman J. Thiagarajan, Rahul Sridhar, Peer-Timo Bremer
MARGIN: Uncovering Deep Neural Networks Using Graph Signal Analysis. Frontiers Big Data 4 (2021)
Ankita Shukla, Rushil Anirudh, Eugene Kur, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Brian K. Spears, Tammy Ma, Pavan K. Turaga
Geometric Priors for Scientific Generative Models in Inertial Confinement Fusion. CoRR (2021)
Rushil Anirudh, Suhas Lohit, Pavan K. Turaga
Generative Patch Priors for Practical Compressive Image Recovery. WACV (2021)
Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Peer-Timo Bremer
MimicGAN: Robust Projection onto Image Manifolds with Corruption Mimicking. Int. J. Comput. Vis. 128 (10) (2020)
Abhinav Bhatele, Jayaraman J. Thiagarajan, Taylor Groves, Rushil Anirudh, Staci A. Smith, Brandon Cook, David K. Lowenthal
The Case of Performance Variability on Dragonfly-based Systems. IPDPS (2020)
Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer
Uncovering interpretable relationships in high-dimensional scientific data through function preserving projections. Mach. Learn. Sci. Technol. 1 (4) (2020)
Gemma J. Anderson, Jim A. Gaffney, Brian K. Spears, Peer-Timo Bremer, Rushil Anirudh, Jayaraman J. Thiagarajan
Meaningful uncertainties from deep neural network surrogates of large-scale numerical simulations. CoRR (2020)
Tejas Gokhale, Rushil Anirudh, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Chitta Baral, Yezhou Yang
Attribute-Guided Adversarial Training for Robustness to Natural Perturbations. CoRR (2020)
Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Timothy C. Germann, Sara Y. Del Valle, Frederick H. Streitz
Accurate Calibration of Agent-based Epidemiological Models with Neural Network Surrogates. CoRR (2020)
Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Rushil Anirudh, Andreas Spanias
Unsupervised Audio Source Separation using Generative Priors. CoRR (2020)
Jayaraman J. Thiagarajan, Bindya Venkatesh, Rushil Anirudh, Peer-Timo Bremer, Jim Gaffney, Gemma Anderson, Brian K. Spears
Designing Accurate Emulators for Scientific Processes using Calibration-Driven Deep Models. CoRR (2020)
Suhas Lohit, Rushil Anirudh, Pavan K. Turaga
Recovering Trajectories of Unmarked Joints in 3D Human Actions Using Latent Space Optimization. CoRR (2020)
Kaushik Koneripalli, Suhas Lohit, Rushil Anirudh, Pavan K. Turaga
Rate-Invariant Autoencoding of Time-Series. ICASSP (2020)
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
Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications. IEEE Trans. Vis. Comput. Graph. 26 (1) (2020)
Jayaraman J. Thiagarajan, Peer-Timo Bremer, Rushil Anirudh, Timothy C. Germann, Sara Y. Del Valle, Frederick H. Streitz
Machine Learning-Powered Mitigation Policy Optimization in Epidemiological Models. CoRR (2020)
Rushil Anirudh, Suhas Lohit, Pavan K. Turaga
Generative Patch Priors for Practical Compressive Image Recovery. CoRR (2020)
Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Brian K. Spears
Improved surrogates in inertial confinement fusion with manifold and cycle consistencies. Proc. Natl. Acad. Sci. USA 117 (18) (2020)
Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Rushil Anirudh, Andreas Spanias
Unsupervised Audio Source Separation Using Generative Priors. INTERSPEECH (2020)
Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Rushil Anirudh, Peer-Timo Bremer, Andreas Spanias
Accurate and Robust Feature Importance Estimation under Distribution Shifts. CoRR (2020)
Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Brian K. Spears
Improved Surrogates in Inertial Confinement Fusion with Manifold and Cycle Consistencies. CoRR (2019)
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
Parallelizing Training of Deep Generative Models on Massive Scientific Datasets. CoRR (2019)
Rushil Anirudh, Hyojin Kim, Jayaraman J. Thiagarajan, K. Aditya Mohan, Kyle Champley
Improving Limited Angle CT Reconstruction with a Robust GAN Prior. CoRR (2019)
Hyojin Kim, Rushil Anirudh, K. Aditya Mohan, Kyle Champley
Extreme Few-view CT Reconstruction using Deep Inference. CoRR (2019)
Jayaraman J. Thiagarajan, Rushil Anirudh, Rahul Sridhar, Peer-Timo Bremer
Unsupervised Dimension Selection Using a Blue Noise Graph Spectrum. ICASSP (2019)
Kowshik Thopalli, Jayaraman J. Thiagarajan, Rushil Anirudh, Pavan K. Turaga
SALT: Subspace Alignment as an Auxiliary Learning Task for Domain Adaptation. CoRR (2019)
Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Timo Bremer
MimicGAN: Robust Projection onto Image Manifolds with Corruption Mimicking. CoRR (2019)
Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer
Function Preserving Projection for Scalable Exploration of High-Dimensional Data. CoRR (2019)
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
Merlin: Enabling Machine Learning-Ready HPC Ensembles. CoRR (2019)
Kowshik Thopalli, Rushil Anirudh, Jayaraman J. Thiagarajan, Pavan K. Turaga
Multiple Subspace Alignment Improves Domain Adaptation. ICASSP (2019)
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
Parallelizing Training of Deep Generative Models on Massive Scientific Datasets. CLUSTER (2019)
Rushil Anirudh, Jayaraman J. Thiagarajan
Bootstrapping Graph Convolutional Neural Networks for Autism Spectrum Disorder Classification. ICASSP (2019)
Jayaraman J. Thiagarajan, Irene Kim, Rushil Anirudh, Peer-Timo Bremer
Understanding Deep Neural Networks through Input Uncertainties. ICASSP (2019)
Rushil Anirudh, Jayaraman J. Thiagarajan, Shusen Liu, Peer-Timo Bremer, Brian K. Spears
Exploring Generative Physics Models with Scientific Priors in Inertial Confinement Fusion. CoRR (2019)
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
Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications. CoRR (2019)
Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Timo Bremer
An Unsupervised Approach to Solving Inverse Problems using Generative Adversarial Networks. CoRR (2018)
Jayaraman J. Thiagarajan, Nikhil Jain, Rushil Anirudh, Alfredo Giménez, Rahul Sridhar, Aniruddha Marathe, Tao Wang, Murali Emani, Abhinav Bhatele, Todd Gamblin
Bootstrapping Parameter Space Exploration for Fast Tuning. ICS (2018)
Kowshik Thopalli, Rushil Anirudh, Jayaraman J. Thiagarajan, Pavan K. Turaga
Multiple Subspace Alignment Improves Domain Adaptation. CoRR (2018)
Qunwei Li, Bhavya Kailkhura, Rushil Anirudh, Yi Zhou, Yingbin Liang, Pramod K. Varshney
MR-GAN: Manifold Regularized Generative Adversarial Networks. CoRR (2018)
Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Timo Bremer
MimicGAN: Corruption-Mimicking for Blind Image Recovery & Adversarial Defense. CoRR (2018)
Rushil Anirudh, Hyojin Kim, Jayaraman J. Thiagarajan, K. Aditya Mohan, Kyle Champley, Timo Bremer
Lose the Views: Limited Angle CT Reconstruction via Implicit Sinogram Completion. CVPR (2018)
Jayaraman J. Thiagarajan, Rushil Anirudh, Bhavya Kailkhura, Nikhil Jain, Tanzima Z. Islam, Abhinav Bhatele, Jae-Seung Yeom, Todd Gamblin
PADDLE: Performance Analysis Using a Data-Driven Learning Environment. IPDPS (2018)
Jayaraman J. Thiagarajan, Rushil Anirudh, Rahul Sridhar, Peer-Timo Bremer
Unsupervised Dimension Selection using a Blue Noise Spectrum. CoRR (2018)
Jayaraman J. Thiagarajan, Irene Kim, Rushil Anirudh, Peer-Timo Bremer
Understanding Deep Neural Networks through Input Uncertainties. CoRR (2018)
Rushil Anirudh, Jayaraman J. Thiagarajan
Bootstrapping Graph Convolutional Neural Networks for Autism Spectrum Disorder Classification. CoRR (2017)
Rushil Anirudh, Jayaraman J. Thiagarajan, Rahul Sridhar, Timo Bremer
Influential Sample Selection: A Graph Signal Processing Approach. CoRR (2017)
Aniruddha Marathe, Rushil Anirudh, Nikhil Jain, Abhinav Bhatele, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Jae-Seung Yeom, Barry Rountree, Todd Gamblin
Performance modeling under resource constraints using deep transfer learning. SC (2017)
Rushil Anirudh, Pavan K. Turaga, Jingyong Su, Anuj Srivastava
Elastic Functional Coding of Riemannian Trajectories. IEEE Trans. Pattern Anal. Mach. Intell. 39 (5) (2017)
Rushil Anirudh, Hyojin Kim, Jayaraman J. Thiagarajan, K. Aditya Mohan, Kyle Champley, Peer-Timo Bremer
Lose The Views: Limited Angle CT Reconstruction via Implicit Sinogram Completion. CoRR (2017)
Rushil Anirudh, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Peer-Timo Bremer
Poisson Disk Sampling on the Grassmannnian: Applications in Subspace Optimization. CVPR Workshops (2017)
Rushil Anirudh, Pavan K. Turaga, Jingyong Su, Anuj Srivastava
Elastic Functional Coding of Riemannian Trajectories. CoRR (2016)
Rushil Anirudh, Jayaraman J. Thiagarajan, Timo Bremer, Hyojin Kim
Lung nodule detection using 3D convolutional neural networks trained on weakly labeled data. Medical Imaging: Computer-Aided Diagnosis (2016)
Rushil Anirudh, Ahnaf Masroor, Pavan K. Turaga
Diversity Promoting Online Sampling for Streaming Video Summarization. CoRR (2016)
Rushil Anirudh, Pavan K. Turaga
Geometry-Based Symbolic Approximation for Fast Sequence Matching on Manifolds. Int. J. Comput. Vis. 116 (2) (2016)
Anirudh Som, Rushil Anirudh, Qiao Wang, Pavan K. Turaga
Riemannian Geometric Approaches for Measuring Movement Quality. CVPR Workshops (2016)
Rushil Anirudh, Vinay Venkataraman, Karthikeyan Natesan Ramamurthy, Pavan K. Turaga
A Riemannian Framework for Statistical Analysis of Topological Persistence Diagrams. CoRR (2016)
Rushil Anirudh, Vinay Venkataraman, Karthikeyan Natesan Ramamurthy, Pavan K. Turaga
A Riemannian Framework for Statistical Analysis of Topological Persistence Diagrams. CVPR Workshops (2016)
Rushil Anirudh, Ahnaf Masroor, Pavan K. Turaga
Diversity promoting online sampling for streaming video summarization. ICIP (2016)
Michael Krzyzaniak, Rushil Anirudh, Vinay Venkataraman, Pavan K. Turaga, Sha Xin Wei
Towards realtime measurement of connectedness in human movement. MOCO (2015)
Rushil Anirudh, Pavan K. Turaga, Jingyong Su, Anuj Srivastava
Elastic functional coding of human actions: From vector-fields to latent variables. CVPR (2015)
Aswin Sivakumar, Rushil Anirudh, Pavan K. Turaga
Geometric Compression of Orientation Signals for Fast Gesture Analysis. DCC (2015)

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Publication Activity (10 Years)

Top Topics

Top Venues

Rushil Anirudh