Rushil Anirudh

Recovering Trajectories of Unmarked Joints in 3D Human Actions Using Latent Space Optimization

Motion capture (mocap) and time-of-flight based sensing of human actions...
12/03/2020 ∙ by Suhas Lohit, et al. ∙ 0 ∙ share

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Generative Patch Priors for Practical Compressive Image Recovery

In this paper, we propose the generative patch prior (GPP) that defines ...
06/18/2020 ∙ by Rushil Anirudh, et al. ∙ 0 ∙ share

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Designing Accurate Emulators for Scientific Processes using Calibration-Driven Deep Models

Predictive models that accurately emulate complex scientific processes c...
05/05/2020 ∙ by Jayaraman J. Thiagarajan, et al. ∙ 4 ∙ share

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Improved Surrogates in Inertial Confinement Fusion with Manifold and Cycle Consistencies

Neural networks have become very popular in surrogate modeling because o...
12/17/2019 ∙ by Rushil Anirudh, et al. ∙ 0 ∙ share

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MimicGAN: Robust Projection onto Image Manifolds with Corruption Mimicking

In the past few years, generative models like Generative Adversarial Net...
12/16/2019 ∙ by Rushil Anirudh, et al. ∙ 9 ∙ share

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Merlin: Enabling Machine Learning-Ready HPC Ensembles

With the growing complexity of computational and experimental facilities...
12/05/2019 ∙ by J. Luc Peterson, et al. ∙ 0 ∙ share

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Extreme Few-view CT Reconstruction using Deep Inference

Reconstruction of few-view x-ray Computed Tomography (CT) data is a high...
10/11/2019 ∙ by Hyojin Kim, et al. ∙ 0 ∙ share

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Parallelizing Training of Deep Generative Models on Massive Scientific Datasets

Training deep neural networks on large scientific data is a challenging ...
10/05/2019 ∙ by Sam Ade Jacobs, et al. ∙ 0 ∙ share

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Exploring Generative Physics Models with Scientific Priors in Inertial Confinement Fusion

There is significant interest in using modern neural networks for scient...
10/03/2019 ∙ by Rushil Anirudh, et al. ∙ 0 ∙ share

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Improving Limited Angle CT Reconstruction with a Robust GAN Prior

Limited angle CT reconstruction is an under-determined linear inverse pr...
10/03/2019 ∙ by Rushil Anirudh, et al. ∙ 0 ∙ share

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Function Preserving Projection for Scalable Exploration of High-Dimensional Data

We present function preserving projections (FPP), a scalable linear proj...
09/25/2019 ∙ by Shusen Liu, et al. ∙ 3 ∙ share

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Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications

With the rapid adoption of machine learning techniques for large-scale a...
07/19/2019 ∙ by Shusen Liu, et al. ∙ 5 ∙ share

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SALT: Subspace Alignment as an Auxiliary Learning Task for Domain Adaptation

Unsupervised domain adaptation aims to transfer and adapt knowledge lear...
06/11/2019 ∙ by Kowshik Thopalli, et al. ∙ 0 ∙ share

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MR-GAN: Manifold Regularized Generative Adversarial Networks

Despite the growing interest in generative adversarial networks (GANs), ...
11/22/2018 ∙ by Qunwei Li, et al. ∙ 0 ∙ share

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MimicGAN: Corruption-Mimicking for Blind Image Recovery & Adversarial Defense

Solving inverse problems continues to be a central challenge in computer...
11/20/2018 ∙ by Rushil Anirudh, et al. ∙ 10 ∙ share

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Multiple Subspace Alignment Improves Domain Adaptation

We present a novel unsupervised domain adaptation (DA) method for cross-...
11/11/2018 ∙ by Kowshik Thopalli, et al. ∙ 0 ∙ share

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Unsupervised Dimension Selection using a Blue Noise Spectrum

Unsupervised dimension selection is an important problem that seeks to r...
10/31/2018 ∙ by Jayaraman J. Thiagarajan, et al. ∙ 0 ∙ share

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Understanding Deep Neural Networks through Input Uncertainties

Techniques for understanding the functioning of complex machine learning...
10/31/2018 ∙ by Jayaraman J. Thiagarajan, et al. ∙ 0 ∙ share

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An Unsupervised Approach to Solving Inverse Problems using Generative Adversarial Networks

Solving inverse problems continues to be a challenge in a wide array of ...
05/18/2018 ∙ by Rushil Anirudh, et al. ∙ 0 ∙ share

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Lose The Views: Limited Angle CT Reconstruction via Implicit Sinogram Completion

Computed Tomography (CT) reconstruction is a fundamental component to a ...
11/28/2017 ∙ by Rushil Anirudh, et al. ∙ 0 ∙ share

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Influential Sample Selection: A Graph Signal Processing Approach

With the growing complexity of machine learning techniques, understandin...
11/15/2017 ∙ by Rushil Anirudh, et al. ∙ 0 ∙ share

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Bootstrapping Graph Convolutional Neural Networks for Autism Spectrum Disorder Classification

Using predictive models to identify patterns that can act as biomarkers ...
04/24/2017 ∙ by Rushil Anirudh, et al. ∙ 0 ∙ share

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Diversity Promoting Online Sampling for Streaming Video Summarization

Many applications benefit from sampling algorithms where a small number ...
10/29/2016 ∙ by Rushil Anirudh, et al. ∙ 0 ∙ share

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A Riemannian Framework for Statistical Analysis of Topological Persistence Diagrams

Topological data analysis is becoming a popular way to study high dimens...
05/28/2016 ∙ by Rushil Anirudh, et al. ∙ 0 ∙ share

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Elastic Functional Coding of Riemannian Trajectories

Visual observations of dynamic phenomena, such as human actions, are oft...
03/07/2016 ∙ by Rushil Anirudh, et al. ∙ 0 ∙ share

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Interactively Test Driving an Object Detector: Estimating Performance on Unlabeled Data

In this paper, we study the problem of `test-driving' a detector, i.e. a...
06/21/2014 ∙ by Rushil Anirudh, et al. ∙ 0 ∙ share

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Rushil Anirudh

Featured Co-authors

Yi Zhou

Di Wang

Yingbin Liang

Jayaraman J. Thiagarajan

Karthikeyan Natesan Ramamurthy

Pavan Turaga

Peter Robinson

Bhavya Kailkhura

Anuj Srivastava

Peer-Timo Bremer

Valerio Pascucci

Recovering Trajectories of Unmarked Joints in 3D Human Actions Using Latent Space Optimization

Generative Patch Priors for Practical Compressive Image Recovery

Designing Accurate Emulators for Scientific Processes using Calibration-Driven Deep Models

Improved Surrogates in Inertial Confinement Fusion with Manifold and Cycle Consistencies

MimicGAN: Robust Projection onto Image Manifolds with Corruption Mimicking

Merlin: Enabling Machine Learning-Ready HPC Ensembles

Extreme Few-view CT Reconstruction using Deep Inference

Parallelizing Training of Deep Generative Models on Massive Scientific Datasets

Exploring Generative Physics Models with Scientific Priors in Inertial Confinement Fusion

Improving Limited Angle CT Reconstruction with a Robust GAN Prior

Function Preserving Projection for Scalable Exploration of High-Dimensional Data

Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications

SALT: Subspace Alignment as an Auxiliary Learning Task for Domain Adaptation

MR-GAN: Manifold Regularized Generative Adversarial Networks

MimicGAN: Corruption-Mimicking for Blind Image Recovery & Adversarial Defense

Multiple Subspace Alignment Improves Domain Adaptation

Unsupervised Dimension Selection using a Blue Noise Spectrum

Understanding Deep Neural Networks through Input Uncertainties

An Unsupervised Approach to Solving Inverse Problems using Generative Adversarial Networks

Lose The Views: Limited Angle CT Reconstruction via Implicit Sinogram Completion

Influential Sample Selection: A Graph Signal Processing Approach

Bootstrapping Graph Convolutional Neural Networks for Autism Spectrum Disorder Classification

Diversity Promoting Online Sampling for Streaming Video Summarization

A Riemannian Framework for Statistical Analysis of Topological Persistence Diagrams

Elastic Functional Coding of Riemannian Trajectories

Interactively Test Driving an Object Detector: Estimating Performance on Unlabeled Data