Organized by the year of publication

2020 2019 2018 2017 2016 2015 2014 Prior-to-2014

## Preprints

K. Thopalli, S. Katoch, P. Turaga, A. Spanias, J. J. Thiagarajan. *Multi-Domain Ensembles for Domain Generalization*. 2021 [coming soon]

R. Subramanyam, M. Heimann, T. S. Jayram, R. Anirudh, B. Kailkhura, J. J. Thiagarajan. *Learning Knowledge Graph Hierarchies for Improving Few-Shot Classification*. 2021 [coming soon]

K. Thopalli, J. J. Thiagarajan, R. Anirudh and P. Turaga. *Revisiting Deep Subspace Alignment for Unsupervised Domain Adaptation*. 2021 [coming soon]

P. Trivedi, M. Heimann, D. Koutra, J. J. Thiagarajan. *Interrogating Paradigms in Self-supervised Graph Representation Learning*. 2021 [coming soon]

M. Olson, R. Anirudh, J. J. Thiagarajan, W. Wong, P. Bremer, S. Liu. *Unsupervised Attribute Alignment for CharacterizingDistribution Shift*. 2021 [coming soon]

T. Gokhale, R. Anirudh, J. J. Thiagarajan, B. Kailkhura, C. Baral. Y. Yang. *ALT: Adversarially Learned Image Transformations for Single-Source Domain Generalization*. 2021 [coming soon]

K. Thopalli, P. Turaga, J. J. Thiagarajan. *Re-labeling Domains Improves Multi-Domain Generalization*. 2021 [coming soon]

A. Shukla *et al. **Geometric Priors for Scientific Generative Models inInertial Confinement Fusion. *2021 [coming soon]

S. Liu, R. Anirudh, J. J. Thiagarajan, P. Bremer. *Sparsity Improves Unsupervised Attribute Discovery in StyleGAN*. 2021 [coming soon]

V. Narayanaswamy, R. Anirudh, I. Kim, Y. Mubarka, A. Spanias, J. J. Thiagarajan. Predicting the Generalization Gap in Deep Models Using Anchoring. 2021 [coming soon]

A. Karargyris *et al.* *MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation*. 2021 [preprint]

J. Peterson *et al.* * Enabling Machine Learning-Ready HPC Ensembles with Merlin. *2021 [preprint]

J. J. Thiagarajan, R. Anirudh. *Δ-UQ: Accurate Uncertainty Quantification via Anchor Marginalization*. 2021 [preprint]

J. J. Thiagarajan, K. Thopalli, D. Rajan, P. Turaga. *Training Calibration-based Counterfactual Explainers for Deep Learning Models in Medical Image Analysis*. 2021 [preprint]

B. Venkatesh, J. J. Thiagarajan. *Heteroscedastic Calibration of Uncertainty Estimators in Deep Learning*. 2021 [preprint]

B. Venkatesh, J. J. Thiagarajan. *Ask-n-Learn: Active Learning via Reliable Gradient Representations for Image Classification*. 2020 [preprint]

B. Venkatesh, J. J. Thiagarajan, K. Thopalli, P. Sattigeri. *Calibrate and Prune: Improving Reliability of Lottery Tickets Through Prediction Calibration*. 2020 [preprint]

J. J. Thiagarajan, P. Sattigeri, D. Rajan, B. Venkatesh. *Calibrating Healthcare AI: Towards Reliable and Interpretable Deep Predictive Models. *2020 [preprint]

S. Katoch, K. Thopalli, J. J. Thiagarajan, P. Turaga, A. Spanias. *Invenio: Discovering Hidden Relationships Between Tasks/Domains using Structured Meta Learning. *2020 [preprint]

[Top]

## 2021

J. J. Thiagarajan, V. Narayanaswamy, D. Rajan, J. Liang, A. Chaudhary, A. Spanias. *Designing Counterfactual Generators using Deep Model Inversion*. Neurips [preprint]

T. Ma *et al.* *Accelerating the rate of discovery: toward high-repetition-rate HED science*. Plasma Physics and Controlled Fusion [paper]

V. Narayanaswamy, J. J. Thiagarajan, A. Spanias. *On the Design of Deep Priors for Unsupervised Audio Restoration* Interspeech [preprint]

R. Anirudh and J. J. Thiagarajan. *Machine Learning Methods for Autism Spectrum Disorder* Classification. Neural Engineering Techniques for Autism Spectrum Disorder. Vol. 1 [chapter]

S. Rao, V. Narayanaswamy, M. Esposito, J. J. Thiagarajan, A. Spanias. *Deep Learning with hyper-parameter tuning for COVID-19 Cough Detection*. International Conference on Information, Intelligence, Systems & Applications [paper]

T. Islam, P. W. Liang, F. Sweeney, C. Pragner, J. J. Thiagarajan, M. Sharmin, S. Ahmed. *College Life is Hard!-Shedding Light on Stress Prediction for Autistic College Students using Data-Driven Analysis*. Computers, Software, and Applications Conference (COMPSAC) [paper]

V. Narayanaswamy, J. J. Thiagarajan, A. Spanias. *Using Deep Image Priors to Generate Counterfactual Explanations*. IEEE ICASSP [preprint]

T. Ramadan, T. Z. Islam, C. Phelps, N. Pinnow, J. J. Thiagarajan. *Comparative Code Structure Analysis using Deep Learning for Performance Prediction*. IEEE International Symposium on Performance Analysis of Systems and Software [paper]

R. Anirudh, J. J. Thiagarajan, R. Sridhar and P-T. Bremer. *MARGIN: Uncovering Deep Neural Networks Using Graph Signal Analysis. *Frontiers Big Data [paper]

U. Shanthamallu, J. J. Thiagarajan, A. Spanias. *Uncertainty-Matching Graph Neural Networks to Defend against Poisoning Attacks. *AAAI [preprint]

J. J. Thiagarajan, V. Narayanaswamy, R. Anirudh, P-T. Bremer, A. Spanias. *Accurate and Robust Feature Importance Estimation under Distribution Shifts*. AAAI [preprint]

T. Gokhale, R. Anirudh, B. Kailkhura, J. J. Thiagarajan*, *C. Baral, Y. Yang. *Attribute-Guided Adversarial Training for Robustness to. Natural Perturbations*. AAAI [preprint]

D. Rajan, J. J. Thiagarajan, S. Kashyap, A. Karargyris. *Self-Training with Improved Regularization for Few-Shot Chest X-Ray Classification**. *SPIE Medical Imaging. [preprint]

[Top]

## 2020

B. Kailkhura, J. J. Thiagarajan, Q. Li, J. Zhang, Y. Zhou, P-T. Bremer. *A statistical Mechanics Framework for Task-Agnostic Sample Design*. Neurips.

J. J. Thiagarajan, B. Venkatesh, R. Anirudh, P-T. Bremer, J. Gaffney, G. Anderson, B. Spears. *Designing Accurate Emulators for Scientific Processes using Calibration-Driven Deep Models*. Nature Communications [preprint]

J. J. Thiagarajan, D. Rajan, S. Katoch and A. Spanias. *DDxNet: A Multi-Speciality Diagnostic Model for ECG and EEG*. Nature Scientific Reports. [paper][code]

J. J. Thiagarajan, B. Venkatesh, D. Rajan, P. Sattigeri. *Improving Reliability of Clinical Models using Prediction Calibration*. MICCAI UNSURE Workshop.

V. Narayanaswamy, J. J. Thiagarajan, R. Anirudh, A. Spanias. *Unsupervised Audio Source Separation using Generative Priors*. Interspeech 2020. [preprint][code]

S. Liu, R. Anirudh, J. J. Thiagarajan, P-T. Bremer. *Uncovering interpretable relationships in high-dimensional scientific data through function preserving projections*. Machine Learning: Science and Technology. [paper][code]

B. Kailkhura, J. J. Thiagarajan, Q. Li, J. Zhang, Y. Zhou, P-T. Bremer. *Task-agnostic Sample Design for Machine Learning*. Workshop on Real World Experiment Design and Active Learning. ICML 2020. [paper]

R. Anirudh, J. J. Thiagarajan, P-T. Bremer, B. Spears. *Improved Surrogates in Intertial Confinement Fusion with Manifold and Cycle Consistencies*. Proceedings of the National Academy of Sciences. [paper]

G. Muniraju, B. Kailkhura, J. J. Thiagarajan and P-T. Bremer. *Coverage-Based Designs Improve Sample Miningand Hyper-Parameter Optimization*. IEEE Transactions on Neural Networks and Learning Systems 2020. [paper]

A. Bhatele, J. J. Thiagarajan, T. Groves, R. Anirudh, S. Smith, B. Cook, D. Lowenthal. *The Case of Performance Variability on Dragonfly-based Systems*. IEEE IPDPS 2020. [paper]

R. Anirudh, J. J. Thiagarajan, B. Kailkhura and P-T. Bremer. MimicGAN: Corruption-Mimicking for Blind Image Recovery and Adversarial Defense. IJCV Special Issue on GANs 2020. [paper]

U. Shanthamallu, J. J. Thiagarajan and A. Spanias. *A Regularized Attention Mechanism for Graph Attention Networks*. IEEE ICASSP 2020. [preprint]

J. J. Thiagarajan, Bindya Venkatesh, Deepta Rajan. *Learn-by-Calibrating: Using Calibration as a Training Objective*. IEEE ICASSP 2020 [preprint]

J. J. Thiagarajan, B. Venkatesh, P. Sattigeri, P-T. Bremer. *Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors. *AAAI Conference on Artificial Intelligence 2020. [paper] [poster]

[Top]

## 2019

J. J. Thiagarajan, S. Kashyap, A. Karagyris. *Distill-to-Label: Weakly Supervised Instance Labeling Using Knowledge Distillation*. IEEE ICMLA 2019. [paper] [slides]

J. J. Thiagarajan. *High-Dimensional Spectral Sampling*. Technical Report 2019. [report]

R. Anirudh, H. Kim, J. J. Thiagarajan, K. A. Mohan, K. Champley. *Improving Limited Angle CT Reconstruction with a Robust GAN Prior*. Neurips Solving Inverse Problems with Deep Learning Workshop 2019. [paper] [poster]

R. Anirudh, J. J. Thiagarajan, S. Liu, P-T. Bremer, B. Spears. *Exploring Generative Physics Models with Scientific Priors in Inertial Confinement Fusion*. Neurips Machine Learning and the Physical Sciences Workshop 2019. [paper] [poster]

V. Narayanaswamy, J. J. Thiagarajan, R. Anirudh, F. Forouzanfar, P-T. Bremer, X. Wu. *Designing Deep Inverse Models for History Matching in Reservoir Simulations*. Neurips Machine Learning and the Physical Sciences Workshop 2019. [paper] [poster]

U. Shanthamallu, Q. Li, J. J. Thiagarajan, R. Anirudh, A. Kaplan, P-T. Bremer. *Modeling Human Brain Connectomes using Structured Neural Networks*. Neurips Graph Representation Learning Workshop 2019. [paper] [poster]

H. Song, J. J. Thiagarajan. *Improving Deep Embeddings for Inferencing with Multi-Layered Graphs*. Deep Graph Learning: Methodologies and Applications, IEEE Big Data 2019. [preprint] [poster]

T. Patki, J. J. Thiagarajan*, *A. Ayala, T. Islam. *Performance optimality or reproducibility: that is the question*. Supercomputing 2019. [paper] [slides]

U. Shanthamallu, J. J. Thiagarajan, H. Song and A. Spanias. *GrAMME: Semi-Supervised Learning using Multi-layered Graph Attention Models**. *IEEE Transactions on Neural Networks and Learning Systems 2019. [paper]

B. Kustowski, J. Gaffney, B. Spears, G. Anderson, J. J. Thiagarajan, R. Anirudh. *Transfer Learning as a Tool for Reducing Simulation Bias: Application to Inertial Confinement Fusion*. IEEE Transactions on Plasma Science 2019. [paper]

S. Liu, D. Wang, D. Maljovec, R. Anirudh, J. J. Thiagarajan, S. A. Jacobs, B. V. Essen, D. Hysom, J. Yeom, J. Gaffney, L. Peterson, H. Bhatia, V. Pascucci, B. Spears, P-T. Bremer. *Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications*. IEEE Transactions on Visualization and Graphics 2019. [paper]

J. J. Thiagarajan, D. Rajan and P. Sattigeri. *Can Deep Clinical Models Handle Real-World Domain Shifts? *KDD Workshop on Applied Data Science for Healthcare 2019. Best Paper Award. [paper] [poster]

S. A. Jacobs, B. V. Essen, D. Hysom, J. Yeom, T. Moon, R. Anirudh, J. J. Thiagarajan, S. Liu, P-T. Bremer, J. Gaffney, T. Benson, P. Robinson, L. Peterson, B. Spears. *Parallelizing Training of Deep Generative Models on Massive Scientific Datasets*. IEEE CLUSTER 2019. [paper]

R. Anirudh and J. J. Thiagarajan. *Bootstrapping Graph Convolutional Neural Networks for Autism Spectrum Disorder Classification*. IEEE ICASSP 2019. [paper] [poster]

J. J. Thiagarajan, I. Kim, R. Anirudh and P-T. Bremer. *Understanding Deep Neural Networks using Input Uncertainties. *IEEE ICASSP 2019. [paper] [slides]

J. J. Thiagarajan, R. Anirudh, R. Sridhar and P-T. Bremer. *Unsupervised Dimension Selection using a Blue Noise Spectrum*. IEEE ICASSP 2019. [paper] [poster]

V. Narayanaswamy, J. J. Thiagarajan, H. Song and A. Spanias. *Designing an Effective Metric Learning Pipeline for Speaker Diarization*. IEEE ICASSP 2019. [paper] [slides]

K. Thopalli, R. Anirudh, J. J. Thiagarajan and P. Turaga. *Multiple Subspace Alignment Improves Domain Adaptation*. IEEE ICASSP 2019. [paper] [poster]

[Top]

## 2018

B. Spears, J. Brase, P-T. Bremer, B. Chen, J. Field, J. Gaffney, M. Kruse, S. Langer, K. Lewis, R. Nora, J. L. Peterson, J. J. Thiagarajan, B. Van Essen and K. Humbird. *Deep learning: A guide for practitioners in the physical sciences*. Physics of Plasmas. [paper]

S. Smith, C. Cromey, D. Lowenthal, J. Domke, N. Jain, J. J. Thiagarajan and A. Bhatele. *Mitigating Inter-Job Interference Using Adaptive Flow-Aware Routing*. International Conference for High Performance Computing, Networking, Storage, and Analysis (SC). [paper]

R. Anirudh, J. J. Thiagarajan, P-T. Bremer and B. Spears. Cyclically Consistent Adversarial Networks for Reliable Surrogates in Intertial Confinement Fusion. Sci-ML Workshop. [paper]

S. Liu, K. Humbird, L. Peterson, J. J. Thiagarajan, B. Spears and P-T. Bremer. Topology-Driven Analysis and Exploration of High-Dimensional Models. Sci-ML Workshop. [paper]

Y. Lin, S. Wang, J. J. Thiagarajan, G. Guthrie and D. Coblentz. *Efficient data-driven geologic feature characterization from pre-stack seismic measurements using randomized machine learning algorithm.* Geophysics Journal International. [paper]

B. Kailkhura, J. J. Thiagarajan, C. Rastogi, P.K. Varshney and P-T. Bremer. *A Spectral Approach for the Design of Experiments: Design. *Journal of Machine Learning Research .[paper]

H. Song, M. Willi, J. J. Thiagarajan, V. Berisha and A. Spanias. *Triplet Network with Attention for Speaker Diarization*. InterSpeech. [paper]

Y. Lin, Y. Wu, S. Wang, J. J. Thiagarajan, G. Guthrie and D. Coblentz. *Solving Inverse Problems in Geophysics Using Machine Learning*. SIAM Annual Meeting. [slides]

J. J. Thiagarajan, N. Jain, R. Anirudh, A. Giminiez, R. Sridhar, A. Marathe, T. Wang, M. Emani, A. Bhatele, T. Gamblin. *Bootstrapping Parameter Space Exploration for Fast Tuning. *International Conference on Supercomputing. [paper]

J. J. Thiagarajan, S. Liu, K. N. Ramamurthy and P.-T. Bremer. *Exploring High‐Dimensional Structure via Axis‐Aligned Decomposition of Linear Projections*. Computer Graphics Forum. [paper]

H. Song, J. J. Thiagarajan, P. Sattigeri and A. Spanias. *Optimizing Kernel Machines Using Deep Learning. *IEEE Transactions on Neural Networks and Learning Systems. [paper]

D. Rajan and J. J. Thiagarajan. *A Generative Modeling Approach to Limited Channel ECG Classification*. International Conference of the IEEE Engineering in Medicine and Biology Society. [paper]

J. J. Thiagarajan, R. Anirudh, B. Kailkhura, N. Jain, T. Islam, A. Bhatele, J. Yeom and T. Gamblin. *PADDLE: Performance Analysis Using a Data-Driven Learning Environment*. IEEE International Parallel and Distributed Processing Symposium (IPDPS). [paper]

S. Liu, P-T. Bremer, J. J. Thiagarajan, V. Srikumar, B. Wang, Y. Livnat and V. Pascucci. *Visual Exploration of Semantic Relationships in Neural Word Embeddings*. IEEE Transactions on Visualization and Computer Graphics. [paper]

[Top]

## 2017

R. Anirudh, H. Kim, J. J. Thiagarajan, K. Champley and P-T. Bremer. *Lose The Views: Limited Angle CT Reconstruction via Implicit Sinogram. *Computer Vision and Pattern Recognition. [paper]

R. Anirudh, J. J. Thiagarajan, R. Sridhar and P-T. Bremer. *MARGIN: Uncovering Deep Neural Networks using Graph Signal Analysis*. [preprint]

A. Marathe, R. Anirudh, N. Jain, A. Bhatele, J. J. Thiagarajan, B. Kailkhura, J. Yeom and T. Gamblin. *Performance modeling under resource constraints using deep transfer learning*. Supercomputing. [paper]

H. Song, D. Rajan, J. J. Thiagarajan and A. Spanias. *Attend and Diagnose: Clinical Time Series Analysis using Attention Models*. AAAI Conference on Artificial Intelligence. [paper]

Y. Lin, S. Wang and J. J. Thiagarajan. *Towards real-time geologic feature detection from seismic measurements using a randomized machine-learning algorithm*. Society of Exploration Geophysicists Meeting. [paper]

P. Zheng, A. Aravkin, K. N. Ramamurthy and J. J. Thiagarajan. *Learning Robust Representations for Computer Vision*. ICCV Workshops. [paper]

R. Anirudh, B. Kailkhura, J. J. Thiagarajan and P-T. Bremer. *Poisson Disk Sampling on the Grassmannnian: Applications in Subspace Optimization*. CVPR Workshops. [paper]

H. Song, J. J. Thiagarajan, P. Sattigeri, K. N. Ramamurthy and J. J. Thiagarajan. *A deep learning approach to multiple kernel fusion*. IEEE ICASSP. [paper]

R. Anirudh, J. J. Thiagarajan, I. Kim and W. Polonik. *Autism Spectrum Disorder Classification using Graph Kernels on Multidimensional Time Series*. [preprint]

Q. Li, B. Kailkhura, J. J. Thiagarajan, Z. Zhang and P. K. Varshney. *Influential Node Detection in Implicit Social Networks using Multi-task Gaussian Copula Models*. NIPS Time Series Workshop. [paper]

[Top]

## 2016

J. J. Thiagarajan, P. Sattigeri, K. N. Ramamurthy and B. Kailkhura. *Robust Local Scaling Using Conditional Quantiles of Graph Similarities*. International Conference on Data Mining Workshops. [paper]

J. J. Thiagarajan, B. Kailkhura, P. Sattigeri and K. N. Ramamurthy. *TreeView: Peeking into Deep Neural Networks Via Feature-Space Partitioning*. NIPS Interpretable Machine Learning in Complex Systems. [paper]

B. Kailkhura, J. J. Thiagarajan, P-T. Bremer and P. K. Varshney. *Stair Blue Noise Sampling. *ACM Transactions on Graphics (Presented at Siggraph Asia). [paper]

J. Yeom, J. J. Thiagarajan, A. Bhatele, G. Bronevetsky and T. Kolve. *Data-driven performance modeling of linear solvers for sparse matrices*. International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computing Systems. [paper]

T. Islam, J. J. Thiagarajan, A. Bhatele, M. Schulz and T. Gamblin. *A Machine Learning Framework for Performance Coverage Analysis of Proxy Applications*. International Conference for High Performance Computing, Networking, Storage and Analysis. [paper]

J. Miller, J. J. Thiagarajan, P-T. Bremer, N. Hoda, D. Stern and R. Mifflin. *Data-Driven Metric Learning for History Matching*. SPE Reservoir Simulation Conference. [paper]

H. Song, J. J. Thiagarajan, K. N. Ramamurthy and A. Spanias. *Auto-context modeling using multiple Kernel learning*. IEEE International Conference on Image Processing. [paper]

B. Kailkhura, J. J. Thiagarajan, P-T. Bremer and P. K. Varshney. *Theoretical guarantees for poisson disk sampling using pair correlation function*. IEEE ICASSP. [paper]

H. Song, J. J. Thiagarajan, K. N. Ramamurthy, A. Spanias and Pavan Turaga. *Consensus inference on mobile phone sensors for activity recognition*. IEEE ICASSP. [paper]

K. N. Ramamurthy, A. Aravkin and J. J. Thiagarajan. *Beyond L2-loss functions for learning sparse models*. IEEE ICASSP. [paper]

R. Anirudh, J. J. Thiagarajan, P-T. Bremer and H. Kim. *Lung nodule detection using 3D convolutional neural networks trained on weakly labeled data*. SPIE Medical Imaging Conference. [paper]

D. Widemann, E. Wang and J. J. Thiagarajan. *ROPE: Recoverable Order-Preserving Embedding of Natural Language*. Technical Report. [preprint]

P. Khanduri, B. Kailkhura, J. J. Thiagarajan and P. K. Varshney. *Universal Collaboration Strategies for Signal Detection: A Sparse Learning Approach*. IEEE Signal Processing Letters. [paper]

P. Sattigeri and J. J. Thiagarajan. *Sparsifying Word Representations for Deep Unordered Sentence Modeling*. ACL Workshop on Representation Learning for NLP. [paper]

S. Liu, P-T. Bremer, J. J. Thiagarajan, B. Wang, B. Summa and V. Pascucci. *The Grassmannian Atlas: A General Framework for Exploring Linear Projections of High‐Dimensional Data*. Computer Graphics Forum. [paper]

[Top]

## 2015

J. J. Thiagarajan, K. N. Ramamurthy and A. Spanias. *Learning Stable Multilevel Dictionaries for Sparse Representations*. IEEE Transactions on Neural Networks and Learning Systems. [paper]

S. Liu, B. Wang, J. J. Thiagarajan, P-T. Bremer and V. Pascucci. *Visual Exploration of High‐Dimensional Data through Subspace Analysis and Dynamic Projections*. Computer Graphics Forum [paper][demo]

K. N. Ramamurthy, A. Aravkin and J. J. Thiagarajan. *Automatic Inference of the Quantile Parameter*. [preprint]

H. Kim, J. J. Thiagarajan and P-T. Bremer. *A Randomized Ensemble Approach to Industrial CT Segmentation*. IEEE International Conference on Computer Vision (ICCV). [paper]

J. J. Thiagarajan and K. N. Ramamurthy. *Subspace learning using consensus on the grassmannian manifold*. IEEE ICASSP. [paper]

S. Ranganath, J. J. Thiagarajan, K. N. Ramamurthy, S. Hu, M. Banavar and A. Spanias. *Undergraduate Signal Processing Laboratories for the Android Operating System. *American Society for Engineering Education. [paper]

A. Bhatele, A. Titus, J. J. Thiagarajan, N. Jain, T. Gamblin, P-T. Bremer, M. Schulz and L. Kale*. Identifying the Culprits Behind Network Congestion*. International Parallel and Distributed Processing Symposium. [paper]

[Top]

## 2014

K. N. Ramamurthy, J. J. Thiagarajan, R. Sridhar, P. Kothandaraman and R. Nachiappan. *Consensus inference with multilayer graphs for multi-modal data*. Asilomar Signals and Systems Conference. [paper]

P. Sattigeri, J. J. Thiagarajan, M. Shah, K. N. Ramamurthy and A. Spanias. *A scalable feature learning and tag prediction framework for natural environment sounds*. Asilomar Signals and Systems Conference. [paper]

S. Liu, B. Wang, J. J. Thiagarajan, P-T. Bremer and V. Pascucci. *Multivariate volume visualization through dynamic projections*. IEEE Symposium on Large Data Analysis and Visualization. [paper]

J. J. Thiagarajan, K. N. Ramamurthy and A. Spanias. *Multiple Kernel Sparse Representations for Supervised and Unsupervised Learning*. IEEE Transactions on Image Processing. [paper]

H. Kim, J. J. Thiagarajan and P-T. Bremer. *Image segmentation using consensus from hierarchical segmentation ensembles*. IEEE International Conference on Image Processing. [paper]

J. J. Thiagarajan, K. N. Ramamurthy, P. Sattigeri, P-T. Bremer and A. Spanias. *Automatic image annotation using inverse maps from semantic embeddings*. IEEE International Conference on Image Processing. [paper]

K. N. Ramamurthy, J. J. Thiagarajan and A. Spanias. *Recovering non-negative and combined sparse representations*. Digital Signal Processing. [paper]

K. N. Ramamurthy, K. Varshney and J. J. Thiagarajan. *Computing persistent homology under random projection*. IEEE Workshop on Statistical Signal Processing. [paper]

J. J. Thiagarajan, P-T. Bremer and K. N. Ramamurthy. *Multiple kernel interpolation for inverting non-linear dimensionality reduction and dimension estimation*. IEEE ICASSP. [paper]

J. J. Thiagarajan, K. N. Ramamurthy, D. Rajan, A. Spanias, A. Puri and D. Frakes. Kernel Sparse Models for Automated Tumor Segmentation. International Journal on Artificial Intelligence Tools. [paper]

[Top]

## Prior-to-2014

J. J. Thiagarajan, K. N. Ramamurthy, P. Sattigeri and A. Spanias. *Boosted dictionaries for image restoration based on sparse representations*. IEEE ICASSP. [paper]

R. Anirudh, K. N. Ramamurthy, J. J. Thiagarajan, P. Turaga and A. Spanias. *A heterogeneous dictionary model for representation and recognition of human actions*. IEEE ICASSP. [paper]

S. Mehta, A. Spanias, J. J. Thiagarajan, M. Banavar, K. N. Ramamurthy, R. Santucci, C. Pattichis, P. Spanias and H. Krishnamoorthi. An integrated graphical environment for web-based learning. ASEE Annual Conference and Exposition. [paper]

A. Spanias, J. J. Thiagarajan, K. N. Ramamurthy, M. Banavar, S. Ranganath, X. Zhang, G. Kalyanasundaram and D. Rajan. *E-book on DSP theory with interactive ios, java, and android simulations*. ASEE Annual Conference and Exposition. [paper]

J. J. Thiagarajan, K. N. Ramamurthy and A. Spanias. *Mixing matrix estimation using discriminative clustering for blind source separation*. Elsevier Digital Signal Processing. [paper]

J. J. Thiagarajan, D. Rajan, K. N. Ramamurthy, D. Frakes and A. Spanias. *Automated tumor segmentation using kernel sparse representations*. International Conference on Bioinformatics and Bioengineering. [paper]

K. N. Ramamurthy, J. J. Thiagarajan, P. Sattigeri and A. Spanias. *Learning dictionaries with graph embedding constraints*. Asilomar Signals and Systems. [paper]

S. Ranganath, J. J. Thiagarajan. K. N. Ramamurthy, S. Hu, M. Banavar and A. Spanias. *Performing signal analysis laboratories using Android devices*. IEEE Frontiers in Education. [paper]

J. J. Thiagarajan, K. N. Ramamurthy, A. Spanias and P. Nasiopoulos. *Learning Multilevel Dictionaries for Compressed Sensing Using Discriminative Clustering*. International Conference on Information Hiding and Multimedia Signal Processing. [paper]

J. J. Thiagarajan, K. N. Ramamurthy and A. Spanias. *Local Sparse Coding for Image Classification and Retrieval*. [preprint]

J. Liu, S. Hu, J. J. Thiagarajan, X. Zhang, S. Ranganath, M. Banavar and A. Spanias. *Interactive DSP laboratories on mobile phones and tablets*. IEEE ICASSP [paper]

P. Sattigeri, J. J. Thiagarajan*, *K. N. Ramamurthy and A. Spanias. *Implementation of a fast image coding and retrieval system using a GPU*. IEEE International Conference on Emerging Signal Processing Applications. [paper]

X. Zhang, D. Vogel, M. Banavar, S. Hu, A. Spanias, P. Spanias and J. J. Thiagarajan. *Using modern mobile technologies in STEM education. *IEEE Frontiers in Education. [paper]

P. Sattigeri, J. J. Thiagarajan, K. N. Ramamurthy, A. Spanias, M. Goryll and T. Thorton. *De-noising and event extraction for silicon pore sensors using matrix decomposition*.

J. J. Thiagarajan, K. N. Ramamurthy and A. Spanias. *Learning dictionaries for local sparse coding in image classification*. Asilomar SSC Conference. [paper]

K. Tsakalis, J. J. Thiagarajan*, *T. Duman, M. Reisslein,G. Tong Zhou, X. Ma and P. Spanias. *Modules and laboratories for a pathways course in signals and systems*. IEEE Frontiers in Education. [paper]

J. Liu, A. Spanias, M. Banavar, J. J. Thiagarajan, K. N. Ramamurthy, S. Hu and X. Zhang. *Interactive signal-processing labs and simulations on iOS devices*. IEEE Frontiers in Education. [paper]

K. N. Ramamurthy, J. J. Thiagarajan and A. Spanias. *Improved sparse coding using manifold projections*. IEEE International Conference on Image Processing. [paper]

P. Sattigeri, K. N. Ramamurthy, J. J. Thiagarajan, M. Goryll, A. Spanias and T. Thornton. *Analyte detection using an ion-channel sensor array*. International Conference on Digital Signal Processing. [paper]

K. N. Ramamurthy, J. J. Thiagarajan, P. Sattigeri, M. Goryll, A. Spanias, T. Thornton and S. Philips. *Transform domain features for ion-channel signal classification*. Biomedical Signal Processing and Control. [paper]

J. J. Thiagarajan, K. N. Ramamurthy and A. Spanias. *Optimality and stability of the K-hyperline clustering algorithm*. Pattern Recognition Letters. [paper]

P. Knee, J. J. Thiagarajan, K. N. Ramamurthy and A. Spanias. *SAR target classification using sparse representations and spatial pyramids*. IEEE RadarCon. [paper]

C. Huang, J. J. Thiagarakan, A. Spanias and C. Pattichis. *A Java-DSP interface for analysis of the MP3 algorithm*. IEEE DSP Conference. [paper]

J. J. Thiagarajan, K. N. Ramamurthy and A. Spanias. *Multilevel dictionary learning for sparse representation of images*. IEEE DSP Conference. [paper]

K. N. Ramamurthy, J. J. Thiagarajan and A. Spanias. *An Interactive Speech Coding Tool using LabVIEW*. IEEE DSP Conference. [paper]

P. Sattigeri, J. J. Thiagarajan, K. N. Ramamurthy, A. Spanias, M. Goryll and T. Thorton. *Robust PSD features for ion-channel signals*.

J. J. Thiagarajan, K. N. Ramamurthy and A. Spanias. *Dimensionality Reduction for Distance Based Video Clustering*. IFIP Advances in Information and Communication Technology. [paper]

P. Sattigeri, J. J. Thiagarajan, K. N. Ramamurthy, B. Konnanath, T. Matthew, A. Spanias, M. Goryll and T. Thorton. *Signal processing for biologically inspired sensors*. International Symposium on Communications, Control and Signal Processing.

J. J. Thiagarajan, K. N. Ramamurthy, P. Knee, A. Spanias and V. Berisha. *Sparse representations for automatic target classification in SAR images*. International Symposium on Communications, Control and Signal Processing.

P. Sattigeri, J. J. Thiagarajan, K. N. Ramamurthy, P. Joshi, A. Spanias, M. Goryll and T. Thorton. *Analysis of Coulter counting data from nanopores using clustering*. .

K. N. Ramamurthy, J. J. Thiagarajan and A. Spanias. *Template Learning using Wavelet Domain Statistical Models*. Research and Development in Intelligent Systems. [paper]

K. N. Ramamurthy, J. J. Thiagarajan and A. Spanias. *Fast image registration with non-stationary Gauss-Markov random field templates*. IEEE International Conference on Image Processing. [paper]

K. N. Ramamurthy, J. J. Thiagarajan,P. Sattigeri, B. Konnanath, A. Spanias, T. Thorton, S. Prasad and S. Philips. Transform domain features for ion-channel signal classification using support vector machines. International Conference on Information Technology and Applications in Biomedicine.

J. J. Thiagarajan, K. N. Ramamurthy, and A. Spanias. *Template Learning using Wavelet Domain Statistical Models*. Research and Development in Intelligent Systems. [paper]

J. J. Thiagarajan, K. N. Ramamurthy and A. Spanias. *Shift-invariant sparse representation of images using learned dictionaries*. IEEE Workshop on Machine Learning for Signal Processing. [paper]

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