Jayaraman J. Thiagarajan

发表

Calibrate and Prune: Improving Reliability of Lottery Tickets Through Prediction Calibration pdf

Bindya Venkatesh, Jayaraman J. Thiagarajan, Kowshik Thopalli, 2020, ArXiv.

Automatic image annotation using inverse maps from semantic embeddings

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Peer-Timo Bremer, 2014, 2014 IEEE International Conference on Image Processing (ICIP).

Uncertainty-Matching Graph Neural Networks to Defend Against Poisoning Attacks pdf

Jayaraman J. Thiagarajan, Uday Shankar Shanthamallu, Andreas Spanias, 2020, AAAI.

Improving Limited Angle CT Reconstruction with a Robust GAN Prior pdf

Hyojin Kim, Jayaraman J. Thiagarajan, Rushil Anirudh, 2019, ArXiv.

Designing Online Laboratories for Power Electronics Courses using J-DSP Software

Andreas Spanias, Raja Ayyanar, Jayaraman J. Thiagarajan, 2011 .

Towards real-time geologic feature detection from seismic measurements using a randomized machine-learning algorithm

Shusen Wang, George D. Guthrie, Jayaraman J. Thiagarajan, 2017 .

Meaningful uncertainties from deep neural network surrogates of large-scale numerical simulations pdf

Rushil Anirudh, Peer-Timo Bremer, Jayaraman J. Thiagarajan, 2020, ArXiv.

Beyond L2-loss functions for learning sparse models

Karthikeyan Natesan Ramamurthy, Aleksandr Y. Aravkin, Jayaraman J. Thiagarajan, 2014, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Bootstrapping Parameter Space Exploration for Fast Tuning

Tao Wang, Rushil Anirudh, Todd Gamblin, 2018, ICS.

Robust Local Scaling Using Conditional Quantiles of Graph Similarities

Karthikeyan Natesan Ramamurthy, Bhavya Kailkhura, Jayaraman J. Thiagarajan, 2016, 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW).

On The Use Of Labview In Signals And Systems

Andreas Spanias, Kostas Tsakalis, Harvey Thornburg, 2009 .

Learning Stable Multilevel Dictionaries for Sparse Representation of Images pdf

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Jayaraman J. Thiagarajan, 2013, ArXiv.

Template learning using wavelet domain statistical models

Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Andreas Spanias, 2009 .

Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors

Peer-Timo Bremer, Bindya Venkatesh, Jayaraman J. Thiagarajan, 2020, AAAI.

Efficient Data-Driven Geologic Feature Detection from Pre-stack Seismic Measurements using Randomized Machine-Learning Algorithm pdf

Shusen Wang, Jayaraman J. Thiagarajan, Youzuo Lin, 2017, Geophysical Journal International.

Supervised local sparse coding of sub-image features for image retrieval

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Jayaraman J. Thiagarajan, 2012, 2012 19th IEEE International Conference on Image Processing.

Interactive Signal Processing Education Applications for the Android Platform

Andreas Spanias, Deepta Rajan, Mahesh K. Banavar, 2019 .

Multiple kernel interpolation for inverting non-linear dimensionality reduction and dimension estimation

Karthikeyan Natesan Ramamurthy, Peer-Timo Bremer, Jayaraman J. Thiagarajan, 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Work in progress — Modules and laboratories for a pathways course in signals and systems

Xiaoli Ma, Martin Reisslein, Kostas Tsakalis, 2011, 2011 Frontiers in Education Conference (FIE).

A scalable feature learning and tag prediction framework for natural environment sounds

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Jayaraman J. Thiagarajan, 2014, 2014 48th Asilomar Conference on Signals, Systems and Computers.

Machine Learning-Powered Mitigation Policy Optimization in Epidemiological Models pdf

Rushil Anirudh, Peer-Timo Bremer, Frederick H. Streitz, 2020, ArXiv.

The Case of Performance Variability on Dragonfly-based Systems

Rushil Anirudh, Abhinav Bhatele, David K. Lowenthal, 2020, 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS).

Work in progress — An interactive web-based quiz that uses the java-DSP editor to enhance student learning experience

Andreas Spanias, Jayaraman J. Thiagarajan, Shalin M Mehta, 2010, 2010 IEEE Frontiers in Education Conference (FIE).

Recovering non-negative and combined sparse representations

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Jayaraman J. Thiagarajan, 2013, Digit. Signal Process..

Improving Reliability of Clinical Models Using Prediction Calibration

Deepta Rajan, Bindya Venkatesh, Jayaraman J. Thiagarajan, 2020, UNSURE/GRAIL@MICCAI.

Consensus inference with multilayer graphs for multi-modal data

Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Rahul Sridhar, 2014, 2014 48th Asilomar Conference on Signals, Systems and Computers.

Optimality and stability of the K-hyperline clustering algorithm

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Jayaraman J. Thiagarajan, 2011, Pattern Recognit. Lett..

Ensemble Sparse Models for Image Analysis pdf

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Jayaraman J. Thiagarajan, 2013, ArXiv.

Attention Models with Random Features for Multi-layered Graph Embeddings pdf

Andreas Spanias, Jayaraman J. Thiagarajan, Uday Shankar Shanthamallu, 2018, ArXiv.

Fast image registration with non-stationary Gauss-Markov random field templates

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Jayaraman J. Thiagarajan, 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

Bootstrapping Graph Convolutional Neural Networks for Autism Spectrum Disorder Classification

Rushil Anirudh, Jayaraman J. Thiagarajan, Rushil Anirudh, 2017, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

A deep learning approach to multiple kernel fusion

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Jayaraman J. Thiagarajan, 2016, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Template Learning using Wavelet Domain Statistical Models

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Jayaraman J. Thiagarajan, 2009, SGAI Conf..

A Machine Learning Framework for Performance Coverage Analysis of Proxy Applications

Martin Schulz, Todd Gamblin, Jayaraman J. Thiagarajan, 2016, SC16: International Conference for High Performance Computing, Networking, Storage and Analysis.

AN INTEGRATED GRAPHICAL ENVIRONMENT FOR WEB-BASED LEARNING

Andreas Spanias, Constantinos S. Pattichis, Mahesh K. Banavar, 2014 .

Multilevel dictionary learning for sparse representation of images

Andreas Spanias, Jayaraman J. Thiagarajan, Karthikeyan N. Ramamurthy, 2011, 2011 Digital Signal Processing and Signal Processing Education Meeting (DSP/SPE).

PADDLE: Performance Analysis Using a Data-Driven Learning Environment

Rushil Anirudh, Todd Gamblin, Bhavya Kailkhura, 2018, 2018 IEEE International Parallel and Distributed Processing Symposium (IPDPS).

Subspace learning using consensus on the grassmannian manifold

Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Visual Exploration of Semantic Relationships in Neural Word Embeddings

Valerio Pascucci, Vivek Srikumar, Shusen Liu, 2018, IEEE Transactions on Visualization and Computer Graphics.

A Look at the Effect of Sample Design on Generalization through the Lens of Spectral Analysis pdf

Qunwei Li, Peer-Timo Bremer, Bhavya Kailkhura, 2019, ArXiv.

Improving Robustness of Attention Models on Graphs pdf

Andreas Spanias, Jayaraman J. Thiagarajan, Uday Shankar Shanthamallu, 2018, ArXiv.

A Spectral Approach for the Design of Experiments: Design, Analysis and Algorithms

Pramod K. Varshney, Peer-Timo Bremer, Bhavya Kailkhura, 2017, J. Mach. Learn. Res..

Computing persistent homology under random projection

Kush R. Varshney, Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, 2014, 2014 IEEE Workshop on Statistical Signal Processing (SSP).

Dimensionality Reduction for Distance Based Video Clustering

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Jayaraman J. Thiagarajan, 2010, AIAI.

Improved sparse coding using manifold projections

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Jayaraman J. Thiagarajan, 2011, 2011 18th IEEE International Conference on Image Processing.

Sparsifying Word Representations for Deep Unordered Sentence Modeling

Jayaraman J. Thiagarajan, Prasanna Sattigeri, P. Sattigeri, 2016, Rep4NLP@ACL.

Distill-to-Label: Weakly Supervised Instance Labeling Using Knowledge Distillation

Satyananda Kashyap, Alexandros Karargyris, Jayaraman J. Thiagarajan, 2019, 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA).

Implementation of a fast image coding and retrieval system using a GPU

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Jayaraman J. Thiagarajan, 2012, 2012 IEEE International Conference on Emerging Signal Processing Applications.

Unsupervised Audio Source Separation using Generative Priors pdf

Rushil Anirudh, Jayaraman J. Thiagarajan, Andreas Spanias, 2020, INTERSPEECH.

Multiple Kernel Sparse Representations for Supervised and Unsupervised Learning

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Jayaraman J. Thiagarajan, 2013, IEEE Transactions on Image Processing.

Learning Robust Representations for Computer Vision

Karthikeyan Natesan Ramamurthy, Aleksandr Y. Aravkin, Peng Zheng, 2017, 2017 IEEE International Conference on Computer Vision Workshops (ICCVW).

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

Rushil Anirudh, Bhavya Kailkhura, Jayaraman J. Thiagarajan, 2018, ArXiv.

Learning dictionaries for local sparse coding in image classification

Andreas Spanias, Jayaraman J. Thiagarajan, A. Spanias, 2011, 2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR).

Poisson Disk Sampling on the Grassmannnian: Applications in Subspace Optimization

Rushil Anirudh, Peer-Timo Bremer, Bhavya Kailkhura, 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

Stair blue noise sampling

Pramod K. Varshney, Peer-Timo Bremer, Bhavya Kailkhura, 2016, ACM Trans. Graph..

AC2011-456: IPHONE/IPADBASEDINTERACTIVELABORATORYFOR SIGNAL PROCESSING IN MOBILE DEVICES

Andreas Spanias, Shuang Hu, Mahesh K. Banavar, 2011 .

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

Hyojin Kim, Rushil Anirudh, Peer-Timo Bremer, 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Calibrating Healthcare AI: Towards Reliable and Interpretable Deep Predictive Models pdf

Deepta Rajan, Bindya Venkatesh, Jayaraman J. Thiagarajan, 2020, ArXiv.

Using Deep Image Priors to Generate Counterfactual Explanations pdf

Jayaraman J. Thiagarajan, Andreas Spanias, Vivek Narayanaswamy, 2020, ArXiv.

iPhone/iPad-Based Interactive Laboratory for Signal Processing in Mobile Devices

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Mahesh K. Banavar, 2011 .

Kernel Sparse Models for Automated Tumor Segmentation pdf

Karthikeyan Natesan Ramamurthy, Deepta Rajan, David H. Frakes, 2013, Int. J. Artif. Intell. Tools.

Finding Optimal Set of Axis-Aligned Projections for High-Dimensional Data

Peer-Timo Bremer, Jayaraman J. Thiagarajan, K N Ramamurthy, 2016 .

Undergraduate Signal Processing Laboratories for the Android Operating System pdf

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Shuang Hu, 2015, ArXiv.

Designing an Effective Metric Learning Pipeline for Speaker Diarization

Andreas Spanias, Jayaraman J. Thiagarajan, Huan Song, 2018, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

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

Sam Ade Jacobs, Valerio Pascucci, Rushil Anirudh, 2019, IEEE Transactions on Visualization and Computer Graphics.

Analysis of the MPEG-1 Layer III (MP3) Algorithm Using MATLAB

Andreas Spanias, Jayaraman J. Thiagarajan, A. Spanias, 2011, Analysis of the MPEG-1 Layer III Algorithm Using MATLAB.

Autism Spectrum Disorder Classification using Graph Kernels on Multidimensional Time Series

Rushil Anirudh, Jayaraman J. Thiagarajan, Irene Kim, 2016, 1611.09897.

Performance Modeling under Resource Constraints Using Deep Transfer Learning

Rushil Anirudh, Todd Gamblin, Bhavya Kailkhura, 2017, SC17: International Conference for High Performance Computing, Networking, Storage and Analysis.

Accurate Calibration of Agent-based Epidemiological Models with Neural Network Surrogates pdf

Rushil Anirudh, Peer-Timo Bremer, Frederick H. Streitz, 2020, Healthcare AI and COVID-19 Workshop.

Machine Learning Meets Visualization to Make Artificial Intelligence Interpretable (Dagstuhl Seminar 19452)

Peer-Timo Bremer, Daniela Oelke, Jayaraman J. Thiagarajan, 2019, Dagstuhl Reports.

Uncovering interpretable relationships in high-dimensional scientific data through function preserving projections

Rushil Anirudh, Peer-Timo Bremer, Jayaraman J. Thiagarajan, 2020, Mach. Learn. Sci. Technol..

MARGIN: Uncovering Deep Neural Networks using Graph Signal Analysis

Rushil Anirudh, Jayaraman J. Thiagarajan, Rahul Sridhar, 2017 .

Controlled Random Search Improves Sample Mining and Hyper-Parameter Optimization pdf

Peer-Timo Bremer, Bhavya Kailkhura, Gowtham Muniraju, 2018, ArXiv.

DDxNet: a deep learning model for automatic interpretation of electronic health records, electrocardiograms and electroencephalograms

Deepta Rajan, Andreas Spanias, Jayaraman J. Thiagarajan, 2020, Scientific Reports.

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

Pavan Turaga, Jayaraman J. Thiagarajan, Kowshik Thopalli, 2019, ArXiv.

Image Understanding Using Sparse Representations

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Pavan K. Turaga, 2014, Synthesis Lectures on Image, Video, and Multimedia Processing.

Unsupervised Dimension Selection Using a Blue Noise Graph Spectrum

Rushil Anirudh, Peer-Timo Bremer, Jayaraman J. Thiagarajan, 2019, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Work in progress: Performing signal analysis laboratories using Android devices

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Shuang Hu, 2012, 2012 Frontiers in Education Conference Proceedings.

Interactive DSP laboratories on mobile phones and tablets

Andreas Spanias, Shuang Hu, Mahesh K. Banavar, 2012, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

An interactive learning environment for DSP

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Mahesh K. Banavar, 2010 .

Heteroscedastic Calibration of Uncertainty Estimators in Deep Learning pdf

Bindya Venkatesh, Jayaraman J. Thiagarajan, Bindya Venkatesh, 2019, ArXiv.

Triplet Network with Attention for Speaker Diarization pdf

Visar Berisha, Andreas Spanias, Jayaraman J. Thiagarajan, 2018, INTERSPEECH.

A Randomized Ensemble Approach to Industrial CT Segmentation

Hyojin Kim, Peer-Timo Bremer, Jayaraman J. Thiagarajan, 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

Multiple Subspace Alignment Improves Domain Adaptation

Rushil Anirudh, Pavan K. Turaga, Jayaraman J. Thiagarajan, 2019, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Coverage-Based Designs Improve Sample Mining and Hyperparameter Optimization

Andreas Spanias, Peer-Timo Bremer, Bhavya Kailkhura, 2018, IEEE Transactions on Neural Networks and Learning Systems.

Transform domain features for ion-channel signal classification using support vector machines

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Jayaraman J. Thiagarajan, 2009, 2009 9th International Conference on Information Technology and Applications in Biomedicine.

TreeView: Peeking into Deep Neural Networks Via Feature-Space Partitioning pdf

Karthikeyan Natesan Ramamurthy, Bhavya Kailkhura, Jayaraman J. Thiagarajan, 2016, ArXiv.

Parallelizing Training of Deep Generative Models on Massive Scientific Datasets

Sam Ade Jacobs, Peer-Timo Bremer, Tom Benson, 2019, 2019 IEEE International Conference on Cluster Computing (CLUSTER).

Self-Training with Improved Regularization for Few-Shot Chest X-Ray Classification pdf

Satyananda Kashyap, Deepta Rajan, Alexandros Karargyris, 2020, ArXiv.

Accurate and Robust Feature Importance Estimation under Distribution Shifts pdf

Rushil Anirudh, Peer-Timo Bremer, Jayaraman J. Thiagarajan, 2020, AAAI.

Exploring High‐Dimensional Structure via Axis‐Aligned Decomposition of Linear Projections

Karthikeyan Natesan Ramamurthy, Shusen Liu, Peer-Timo Bremer, 2018, Comput. Graph. Forum.

Improved Deep Embeddings for Inferencing with Multi-Layered Graphs

Jayaraman J. Thiagarajan, Huan Song, Huan Song, 2019, 2019 IEEE International Conference on Big Data (Big Data).

Visual Exploration of High‐Dimensional Data through Subspace Analysis and Dynamic Projections

Valerio Pascucci, Shusen Liu, Bei Wang, 2015, Comput. Graph. Forum.

Invenio: Discovering Hidden Relationships Between Tasks/Domains Using Structured Meta Learning pdf

Pavan Turaga, Jayaraman J. Thiagarajan, Kowshik Thopalli, 2019, ArXiv.

AC2012-5201: WORK-IN-PROGRESS:USINGMODERNMOBILETECH- NOLOGIES IN STEM EDUCATION

Andreas Spanias, Shuang Hu, Mahesh K. Banavar, 2012 .

Attend and Diagnose: Clinical Time Series Analysis using Attention Models pdf

Andreas Spanias, Deepta Rajan, Jayaraman J. Thiagarajan, 2017, AAAI.

Audio Source Separation via Multi-Scale Learning with Dilated Dense U-Nets pdf

Andreas Spanias, Jayaraman J. Thiagarajan, Sameeksha Katoch, 2019, ArXiv.

Image segmentation using consensus from hierarchical segmentation ensembles

Hyojin Kim, Peer-Timo Bremer, Jayaraman J. Thiagarajan, 2014, 2014 IEEE International Conference on Image Processing (ICIP).

Multivariate volume visualization through dynamic projections

Valerio Pascucci, Shusen Liu, Bei Wang, 2014, 2014 IEEE 4th Symposium on Large Data Analysis and Visualization (LDAV).

Improved surrogates in inertial confinement fusion with manifold and cycle consistencies

Rushil Anirudh, Peer-Timo Bremer, Jayaraman J. Thiagarajan, 2019, Proceedings of the National Academy of Sciences.

Consensus inference on mobile phone sensors for activity recognition

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Pavan K. Turaga, 2016, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Work in progress — Interactive signal-processing labs and simulations on iOS devices

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Shuang Hu, 2011, 2011 Frontiers in Education Conference (FIE).

A heterogeneous dictionary model for representation and recognition of human actions

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Rushil Anirudh, 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

Boosted dictionaries for image restoration based on sparse representations

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Jayaraman J. Thiagarajan, 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

MimicGAN: Robust Projection onto Image Manifolds with Corruption Mimicking

Rushil Anirudh, Bhavya Kailkhura, Jayaraman J. Thiagarajan, 2020, International Journal of Computer Vision.

Automated tumor segmentation using kernel sparse representations

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Deepta Rajan, 2012, 2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE).

Designing accurate emulators for scientific processes using calibration-driven deep models

Rushil Anirudh, Peer-Timo Bremer, Bindya Venkatesh, 2020, Nature Communications.

GrAMME: Semisupervised Learning Using Multilayered Graph Attention Models

Andreas Spanias, Jayaraman J. Thiagarajan, Uday Shankar Shanthamallu, 2018, IEEE Transactions on Neural Networks and Learning Systems.

Learn-By-Calibrating: Using Calibration As A Training Objective

Deepta Rajan, Bindya Venkatesh, Jayaraman J. Thiagarajan, 2019, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Exploring Generative Physics Models with Scientific Priors in Inertial Confinement Fusion pdf

Peer-Timo Bremer, Jayaraman J. Thiagarajan, Rushil Anirudh, 2019, ArXiv.

Function Preserving Projection for Scalable Exploration of High-Dimensional Data pdf

Peer-Timo Bremer, Jayaraman J. Thiagarajan, Rushil Anirudh, 2019, ArXiv.

Mitigating Inter-Job Interference Using Adaptive Flow-Aware Routing

Jens Domke, David K. Lowenthal, Jayaraman J. Thiagarajan, 2018, SC18: International Conference for High Performance Computing, Networking, Storage and Analysis.

Understanding Deep Neural Networks through Input Uncertainties

Rushil Anirudh, Peer-Timo Bremer, Jayaraman J. Thiagarajan, 2018, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Work-in-Progress: Using Modern Mobile Technologies in STEM Education

Andreas Spanias, Mahesh K. Banavar, Xue Zhang, 2012 .

A Statistical Mechanics Framework for Task-Agnostic Sample Design in Machine Learning

Bhavya Kailkhura, Yi Zhou, Jize Zhang, 2020, Neural Information Processing Systems.

A Generative Modeling Approach to Limited Channel ECG Classification

Deepta Rajan, Jayaraman J. Thiagarajan, Deepta Rajan, 2018, 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

An Unsupervised Approach to Solving Inverse Problems using Generative Adversarial Networks pdf

Rushil Anirudh, Bhavya Kailkhura, Jayaraman J. Thiagarajan, 2018, ArXiv.

Improved Community Detection using Deep Embeddings from Multilayer Graphs pdf

Jayaraman J. Thiagarajan, Huan Song, 2018, ArXiv.

A Java-DSP interface for analysis of the MP3 algorithm

Andreas Spanias, Constantinos Pattichis, Jayaraman J. Thiagarajan, 2011, 2011 Digital Signal Processing and Signal Processing Education Meeting (DSP/SPE).

Auto-context modeling using multiple Kernel learning

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Jayaraman J. Thiagarajan, 2016, 2016 IEEE International Conference on Image Processing (ICIP).

Attribute-Guided Adversarial Training for Robustness to Natural Perturbations pdf

Chitta Baral, Rushil Anirudh, Bhavya Kailkhura, 2020, ArXiv.

Universal Collaboration Strategies for Signal Detection: A Sparse Learning Approach

Pramod K. Varshney, Prashant Khanduri, Bhavya Kailkhura, 2016, IEEE Signal Processing Letters.

Identifying the Culprits Behind Network Congestion

Laxmikant V. Kalé, Martin Schulz, Todd Gamblin, 2015, 2015 IEEE International Parallel and Distributed Processing Symposium.

An interactive speech coding tool using LabVIEW™

Andreas Spanias, Jayaraman J. Thiagarajan, Karthikeyan N. Ramamurthy, 2011, 2011 Digital Signal Processing and Signal Processing Education Meeting (DSP/SPE).

Measuring glomerular number from kidney MRI images

Karthikeyan Natesan Ramamurthy, Andreas Spanias, David H. Frakes, 2016, SPIE Medical Imaging.

Data-Driven Performance Modeling of Linear Solvers for Sparse Matrices

Greg Bronevetsky, Jayaraman J. Thiagarajan, Tzanio V. Kolev, 2016, 2016 7th International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS).

E-Book on DSP Theory with Interactive iOS, Java, and Android Simulations

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Deepta Rajan, 2013 .

Learning Multilevel Dictionaries for Compressed Sensing Using Discriminative Clustering

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Panos Nasiopoulos, 2012, 2012 Eighth International Conference on Intelligent Information Hiding and Multimedia Signal Processing.

Influential Node Detection in Implicit Social Networks using Multi-task Gaussian Copula Models pdf

Pramod K. Varshney, Qunwei Li, Bhavya Kailkhura, 2016, NIPS Time Series Workshop.

Theoretical guarantees for poisson disk sampling using pair correlation function

Pramod K. Varshney, Peer-Timo Bremer, Bhavya Kailkhura, 2016, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Can Deep Clinical Models Handle Real-World Domain Shifts? pdf

Deepta Rajan, Jayaraman J. Thiagarajan, Prasanna Sattigeri, 2018, ArXiv.

Learning dictionaries with graph embedding constraints

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Jayaraman J. Thiagarajan, 2012, 2012 Conference Record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR).

Sparse Representations for Pattern Classification using Learned Dictionaries

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Jayaraman J. Thiagarajan, 2008, SGAI Conf..

Performance optimality or reproducibility: that is the question

Tapasya Patki, Jayaraman J. Thiagarajan, Alexis Ayala, 2019, SC.

Ask-n-Learn: Active Learning via Reliable Gradient Representations for Image Classification pdf

Bindya Venkatesh, Jayaraman J. Thiagarajan, Bindya Venkatesh, 2020, ArXiv.

Lung nodule detection using 3D convolutional neural networks trained on weakly labeled data

Hyojin Kim, Rushil Anirudh, Jayaraman J. Thiagarajan, 2016, SPIE Medical Imaging.

Mixing matrix estimation using discriminative clustering for blind source separation

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Jayaraman J. Thiagarajan, 2013, Digit. Signal Process..

Improved Deep Embeddings for Inferencing with Multi-Layered Networks

Jayaraman J. Thiagarajan, Huan Song, Huan Song, 2018 .

Learning Stable Multilevel Dictionaries for Sparse Representations

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Jayaraman J. Thiagarajan, 2013, IEEE Transactions on Neural Networks and Learning Systems.

AC 2012-4755: UNDERGRADUATE SIGNAL PROCESSING LABORATO- RIES FOR THE ANDROID OPERATING SYSTEM

Andreas Spanias, Shuang Hu, Mahesh K. Banavar, 2012 .

Designing Counterfactual Generators using Deep Model Inversion pdf

Andreas Spanias, Deepta Rajan, Jayaraman J. Thiagarajan, 2021, NeurIPS.

On the Design of Deep Priors for Unsupervised Audio Restoration pdf

Andreas Spanias, Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, 2021, Interspeech.

Self-training with improved regularization for sample-efficient chest x-ray classification

Satyananda Kashyap, Deepta Rajan, Alexandros Karargyris, 2021, Medical Imaging.

Improving Multi-Domain Generalization through Domain Re-labeling pdf

Pavan Turaga, Jayaraman J. Thiagarajan, Sameeksha Katoch, 2021, ArXiv.

Federated benchmarking of medical artificial intelligence with MedPerf pdf

Satyananda Kashyap, Nicolas Padoy, Grigori Fursin, 2021, Nature Machine Intelligence.

College Life is Hard! - Shedding Light on Stress Prediction for Autistic College Students using Data-Driven Analysis

Moushumi Sharmin, Jayaraman J. Thiagarajan, Shameem Ahmed, 2021, 2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC).

Comparative Code Structure Analysis using Deep Learning for Performance Prediction

Jayaraman J. Thiagarajan, Tanzima Z. Islam, Nathan Pinnow, 2021, 2021 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS).

Training calibration-based counterfactual explainers for deep learning models in medical image analysis

Deepta Rajan, Pavan Turaga, Jayaraman J. Thiagarajan, 2021, Scientific Reports.

Loss Estimators Improve Model Generalization pdf

Andreas Spanias, Deepta Rajan, Jayaraman J. Thiagarajan, 2021, ArXiv.

Sparse representations for automatic target classification in SAR images

Jayaraman J. Thiagarajan, K. Ramamurthy, P. Knee, 2010, 2010 4th International Symposium on Communications, Control and Signal Processing (ISCCSP).

Local Sparse Coding for Image Classification and Retrieval

Jayaraman J. Thiagarajan, K. Ramamurthy, A. Spanias, 2011 .

Transfer Learning as a Tool for Reducing Simulation Bias: Application to Inertial Confinement Fusion

Rushil Anirudh, Jim Gaffney, Jayaraman J. Thiagarajan, 2020, IEEE Transactions on Plasma Science.

Shift-invariant sparse representation of images using learned dictionaries

Jayaraman J. Thiagarajan, A. Spanias, K. Ramamurthy, 2008, 2008 IEEE Workshop on Machine Learning for Signal Processing.

Understanding Behavior of Clinical Models under Domain Shifts

Deepta Rajan, Jayaraman J. Thiagarajan, Prasanna Sattigeri, 2018 .

Transform domain features for ion-channel signal classification using support vector machines

Jayaraman J. Thiagarajan, T. Thornton, P. Sattigeri, 2009 .

Robust PSD features for ion-channel signals

Andreas Spanias, Jayaraman J. Thiagarajan, Prasanna Sattigeri, 2011 .

Automatic Inference of the Quantile Parameter

Karthikeyan Natesan Ramamurthy, Aleksandr Y. Aravkin, Jayaraman J. Thiagarajan, 2015 .

SAR target classification using sparse representations and spatial pyramids

Karthikeyan Natesan Ramamurthy, Andreas Spanias, Jayaraman J. Thiagarajan, 2011, 2011 IEEE RadarCon (RADAR).

Designing Deep Inverse Models for History Matching in Reservoir Simulations

Rushil Anirudh, Peer-Timo Bremer, Jayaraman J. Thiagarajan, 2019 .

Visual Exploration of High-Dimensional Data : Subspace Analysis through Dynamic Projections

Valerio Pascucci, Peer-Timo Bremer, Jayaraman J. Thiagarajan, 2014 .

Analyzing Inter-Job Contention in Dragonfly Networks

Peer-Timo Bremer, David K. Lowenthal, Jayaraman J. Thiagarajan, 2016 .

De-noising and event extraction for silicon pore sensors using matrix decomposition

Andreas Spanias, Jayaraman J. Thiagarajan, Prasanna Sattigeri, 2012 .

Signal processing for biologically inspired sensors

Jayaraman J. Thiagarajan, T. Thornton, P. Sattigeri, 2010, 2010 4th International Symposium on Communications, Control and Signal Processing (ISCCSP).

Analyte detection using an ion-channel sensor array

Jayaraman J. Thiagarajan, T. Thornton, P. Sattigeri, 2011, 2011 17th International Conference on Digital Signal Processing (DSP).

Influential Sample Selection: A Graph Signal Processing Approach

Jayaraman J. Thiagarajan, R. Sridhar, Rushil Anirudh, 2017, ArXiv.

Linear Projections Axis-Aligned Projections Animated Projection Transition ( a ) ( b )

Jayaraman J. Thiagarajan, P. Bremer, K. Ramamurthy, 2017 .

Domain Alignment Meets Fully Test-Time Adaptation

Jayaraman J. Thiagarajan, P. Turaga, Kowshik Thopalli, 2022, ACML.

Mortality after emergency abdominal surgery in a non‐metropolitan Australian centre

Jayaraman J. Thiagarajan, G. Maddern, M. Wichmann, 2018, The Australian journal of rural health.

MedPerf: Open Benchmarking Platform for Medical AI using Federated Evaluation (npj Digital Medicine, arxiv)

Jayaraman J. Thiagarajan, Daniel J. Beutel, Micah J. Sheller, 2022 .

MimicGAN: Robust Projection onto Image Manifolds with Corruption Mimicking

Jayaraman J. Thiagarajan, B. Kailkhura, Rushil Anirudh, 2019, International Journal of Computer Vision.

Improved StyleGAN-v2 based Inversion for Out-of-Distribution Images

Jayaraman J. Thiagarajan, A. Spanias, M. Naufel, 2022, ICML.

Deep Learning with hyper-parameter tuning for COVID-19 Cough Detection

Andreas Spanias, Jayaraman J. Thiagarajan, Vivek Narayanaswamy, 2021, 2021 12th International Conference on Information, Intelligence, Systems & Applications (IISA).

Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors

Jayaraman J. Thiagarajan, P. Sattigeri, P. Bremer, 2019, AAAI.

Sparse Methods in Image Understanding and Computer Vision

Jayaraman J. Thiagarajan, Jayaraman Jayaraman Thiagarajan, 2013 .

Multi-Domain Ensembles for Domain Generalization

Jayaraman J. Thiagarajan, P. Turaga, A. Spanias, 2021 .

Calibrate and Prune: Improving Reliability of Lottery Tickets Through Prediction Calibration

Jayaraman J. Thiagarajan, P. Sattigeri, Bindya Venkatesh, 2020, ArXiv.

Improving Limited Angle CT Reconstruction with a Robust GAN Prior

Jayaraman J. Thiagarajan, Rushil Anirudh, Hyojin Kim, 2019, ArXiv.

Attribute-Guided Adversarial Training for Robustness to Natural Perturbations

Jayaraman J. Thiagarajan, Chitta Baral, B. Kailkhura, 2020, AAAI.

Comparative Code Structure Analysis using Deep Learning for Performance Prediction

Jayaraman J. Thiagarajan, T. Islam, Tarek Ramadan, 2021, 2021 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS).

Invenio: Discovering Hidden Relationships Between Tasks/Domains Using Structured Meta Learning

Jayaraman J. Thiagarajan, A. Spanias, P. Turaga, 2019, ArXiv.

A Regularized Attention Mechanism for Graph Attention Networks

Jayaraman J. Thiagarajan, A. Spanias, U. Shanthamallu, 2018, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).