Jayaraman J. Thiagarajan

Orcid: 0000-0002-8517-5816

According to our database1, Jayaraman J. Thiagarajan authored at least 188 papers between 2008 and 2024.

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Bibliography

2024
On The Role of Prompt Construction In Enhancing Efficacy and Efficiency of LLM-Based Tabular Data Generation.
CoRR, 2024

Enhancing Accuracy and Parameter-Efficiency of Neural Representations for Network Parameterization.
CoRR, 2024

Speeding Up Image Classifiers with Little Companions.
CoRR, 2024

On the Use of Anchoring for Training Vision Models.
CoRR, 2024

PAGER: Accurate Failure Characterization in Deep Regression Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

On Estimating Link Prediction Uncertainty Using Stochastic Centering.
Proceedings of the IEEE International Conference on Acoustics, 2024

Exploring the Utility of Clip Priors for Visual Relationship Prediction.
Proceedings of the IEEE International Conference on Acoustics, 2024

The Double-Edged Sword Of Ai Safety: Balancing Anomaly Detection and OOD Generalization Via Model Anchoring.
Proceedings of the IEEE International Conference on Acoustics, 2024

DECIDER: Leveraging Foundation Model Priors for Improved Model Failure Detection and Explanation.
Proceedings of the Computer Vision - ECCV 2024, 2024

'Eyes of a Hawk and Ears of a Fox': Part Prototype Network for Generalized Zero-Shot Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Federated benchmarking of medical artificial intelligence with MedPerf.
Nat. Mac. Intell., July, 2023

Transformer-Powered Surrogates Close the ICF Simulation-Experiment Gap with Extremely Limited Data.
CoRR, 2023

PAGER: A Framework for Failure Analysis of Deep Regression Models.
CoRR, 2023

CREPE: Learnable Prompting With CLIP Improves Visual Relationship Prediction.
CoRR, 2023

The Surprising Effectiveness of Deep Orthogonal Procrustes Alignment in Unsupervised Domain Adaptation.
IEEE Access, 2023

Improving Object Detectors by Exploiting Bounding Boxes for Augmentation Design.
IEEE Access, 2023

Contrastive Knowledge-Augmented Meta-Learning for Few-Shot Classification.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Improving Diversity with Adversarially Learned Transformations for Domain Generalization.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Know Your Space: Inlier and Outlier Construction for Calibrating Medical OOD Detectors.
Proceedings of the Medical Imaging with Deep Learning, 2023

Target-Aware Generative Augmentations for Single-Shot Adaptation.
Proceedings of the International Conference on Machine Learning, 2023

A Closer Look at Model Adaptation using Feature Distortion and Simplicity Bias.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

InterAug: A Tuning-Free Augmentation Policy for Data-Efficient and Robust Object Detection.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Exploring Inlier and Outlier Specification for Improved Medical OOD Detection.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

DOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstruction.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

A Closer Look At Scoring Functions And Generalization Prediction.
Proceedings of the IEEE International Conference on Acoustics, 2023

Single-Shot Domain Adaptation via Target-Aware Generative Augmentations.
Proceedings of the IEEE International Conference on Acoustics, 2023

Cross-GAN Auditing: Unsupervised Identification of Attribute Level Similarities and Differences Between Pretrained Generative Models.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Suppressing simulation bias in multi-modal data using transfer learning.
Mach. Learn. Sci. Technol., 2022

A biology-informed similarity metric for simulated patches of human cell membrane.
Mach. Learn. Sci. Technol., 2022

Instruction Tools for Signal Processing and Machine Learning for Ion-Channel Sensors.
Int. J. Virtual Pers. Learn. Environ., 2022

Improving Single-Stage Object Detectors for Nighttime Pedestrian Detection.
Int. J. Pattern Recognit. Artif. Intell., 2022

Enabling machine learning-ready HPC ensembles with Merlin.
Future Gener. Comput. Syst., 2022

On-the-fly Object Detection using StyleGAN with CLIP Guidance.
CoRR, 2022

Single-Shot Domain Adaptation via Target-Aware Generative Augmentation.
CoRR, 2022

Analyzing Data-Centric Properties for Contrastive Learning on Graphs.
CoRR, 2022

Exploring the Design of Adaptation Protocols for Improved Generalization and Machine Learning Safety.
CoRR, 2022

Revisiting Inlier and Outlier Specification for Improved Out-of-Distribution Detection.
CoRR, 2022

Revisiting Deep Subspace Alignment for Unsupervised Domain Adaptation.
CoRR, 2022

Analyzing Data-Centric Properties for Graph Contrastive Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Single Model Uncertainty Estimation via Stochastic Data Centering.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Machine Learning-Powered Mitigation Policy Optimization in Epidemiological Models.
Proceedings of the 1st Workshop on Healthcare AI and COVID-19, 2022

Improved StyleGAN-v2 based Inversion for Out-of-Distribution Images.
Proceedings of the International Conference on Machine Learning, 2022

Accurate Calibration of Agent-based Epidemiological Models with Neural Network Surrogates.
Proceedings of the 1st Workshop on Healthcare AI and COVID-19, 2022

Predicting the Generalization Gap in Deep Models using Anchoring.
Proceedings of the IEEE International Conference on Acoustics, 2022

Sparsity Improves Unsupervised Attribute Discovery in Stylegan.
Proceedings of the IEEE International Conference on Acoustics, 2022

Domain Alignment Meets Fully Test-Time Adaptation.
Proceedings of the Asian Conference on Machine Learning, 2022

Out of Distribution Detection via Neural Network Anchoring.
Proceedings of the Asian Conference on Machine Learning, 2022

2021
Coverage-Based Designs Improve Sample Mining and Hyperparameter Optimization.
IEEE Trans. Neural Networks Learn. Syst., 2021

COVID-19 detection using cough sound analysis and deep learning algorithms.
Intell. Decis. Technol., 2021

Preventing Failures by Dataset Shift Detection in Safety-Critical Graph Applications.
Frontiers Artif. Intell., 2021

MARGIN: Uncovering Deep Neural Networks Using Graph Signal Analysis.
Frontiers Big Data, 2021

Improving Multi-Domain Generalization through Domain Re-labeling.
CoRR, 2021

Geometric Priors for Scientific Generative Models in Inertial Confinement Fusion.
CoRR, 2021

Δ-UQ: Accurate Uncertainty Quantification via Anchor Marginalization.
CoRR, 2021

MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation.
CoRR, 2021

Designing Counterfactual Generators using Deep Model Inversion.
CoRR, 2021

Transfer learning suppresses simulation bias in predictive models built from sparse, multi-modal data.
CoRR, 2021

Loss Estimators Improve Model Generalization.
CoRR, 2021

Designing Counterfactual Generators using Deep Model Inversion.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Self-training with improved regularization for sample-efficient chest x-ray classification.
Proceedings of the Medical Imaging 2021: Computer-Aided Diagnosis, 2021

Comparative Code Structure Analysis using Deep Learning for Performance Prediction.
Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2021

On the Design of Deep Priors for Unsupervised Audio Restoration.
Proceedings of the 22nd Annual Conference of the International Speech Communication Association, Interspeech 2021, Brno, Czechia, August 30, 2021

Deep Learning with hyper-parameter tuning for COVID-19 Cough Detection.
Proceedings of the 12th International Conference on Information, 2021

Using Deep Image Priors to Generate Counterfactual Explanations.
Proceedings of the IEEE International Conference on Acoustics, 2021

College Life is Hard! - Shedding Light on Stress Prediction for Autistic College Students using Data-Driven Analysis.
Proceedings of the IEEE 45th Annual Computers, Software, and Applications Conference, 2021

Accurate and Robust Feature Importance Estimation under Distribution Shifts.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Uncertainty-Matching Graph Neural Networks to Defend Against Poisoning Attacks.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Attribute-Guided Adversarial Training for Robustness to Natural Perturbations.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications.
IEEE Trans. Vis. Comput. Graph., 2020

GrAMME: Semisupervised Learning Using Multilayered Graph Attention Models.
IEEE Trans. Neural Networks Learn. Syst., 2020

Improved surrogates in inertial confinement fusion with manifold and cycle consistencies.
Proc. Natl. Acad. Sci. USA, 2020

Uncovering interpretable relationships in high-dimensional scientific data through function preserving projections.
Mach. Learn. Sci. Technol., 2020

MimicGAN: Robust Projection onto Image Manifolds with Corruption Mimicking.
Int. J. Comput. Vis., 2020

Meaningful uncertainties from deep neural network surrogates of large-scale numerical simulations.
CoRR, 2020

Ask-n-Learn: Active Learning via Reliable Gradient Representations for Image Classification.
CoRR, 2020

Designing Accurate Emulators for Scientific Processes using Calibration-Driven Deep Models.
CoRR, 2020

Self-Training with Improved Regularization for Few-Shot Chest X-Ray Classification.
CoRR, 2020

Calibrating Healthcare AI: Towards Reliable and Interpretable Deep Predictive Models.
CoRR, 2020

Calibrate and Prune: Improving Reliability of Lottery Tickets Through Prediction Calibration.
CoRR, 2020

A Statistical Mechanics Framework for Task-Agnostic Sample Design in Machine Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Improving Reliability of Clinical Models Using Prediction Calibration.
Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis, 2020

The Case of Performance Variability on Dragonfly-based Systems.
Proceedings of the 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2020

Unsupervised Audio Source Separation Using Generative Priors.
Proceedings of the 21st Annual Conference of the International Speech Communication Association, 2020

Learn-By-Calibrating: Using Calibration As A Training Objective.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

A Regularized Attention Mechanism for Graph Attention Networks.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Treeview and Disentangled Representations for Explaining Deep Neural Networks Decisions.
Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Machine Learning Meets Visualization to Make Artificial Intelligence Interpretable (Dagstuhl Seminar 19452).
Dagstuhl Reports, 2019

Merlin: Enabling Machine Learning-Ready HPC Ensembles.
CoRR, 2019

Invenio: Discovering Hidden Relationships Between Tasks/Domains Using Structured Meta Learning.
CoRR, 2019

Heteroscedastic Calibration of Uncertainty Estimators in Deep Learning.
CoRR, 2019

Exploring Generative Physics Models with Scientific Priors in Inertial Confinement Fusion.
CoRR, 2019

Improving Limited Angle CT Reconstruction with a Robust GAN Prior.
CoRR, 2019

Function Preserving Projection for Scalable Exploration of High-Dimensional Data.
CoRR, 2019

SALT: Subspace Alignment as an Auxiliary Learning Task for Domain Adaptation.
CoRR, 2019

A Look at the Effect of Sample Design on Generalization through the Lens of Spectral Analysis.
CoRR, 2019

Audio Source Separation via Multi-Scale Learning with Dilated Dense U-Nets.
CoRR, 2019

Performance optimality or reproducibility: that is the question.
Proceedings of the International Conference for High Performance Computing, 2019

Distill-to-Label: Weakly Supervised Instance Labeling Using Knowledge Distillation.
Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

Multiple Subspace Alignment Improves Domain Adaptation.
Proceedings of the IEEE International Conference on Acoustics, 2019

Understanding Deep Neural Networks through Input Uncertainties.
Proceedings of the IEEE International Conference on Acoustics, 2019

Unsupervised Dimension Selection Using a Blue Noise Graph Spectrum.
Proceedings of the IEEE International Conference on Acoustics, 2019

Designing an Effective Metric Learning Pipeline for Speaker Diarization.
Proceedings of the IEEE International Conference on Acoustics, 2019

Bootstrapping Graph Convolutional Neural Networks for Autism Spectrum Disorder Classification.
Proceedings of the IEEE International Conference on Acoustics, 2019

Parallelizing Training of Deep Generative Models on Massive Scientific Datasets.
Proceedings of the 2019 IEEE International Conference on Cluster Computing, 2019

Improved Deep Embeddings for Inferencing with Multi-Layered Graphs.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018
Visual Exploration of Semantic Relationships in Neural Word Embeddings.
IEEE Trans. Vis. Comput. Graph., 2018

Optimizing Kernel Machines Using Deep Learning.
IEEE Trans. Neural Networks Learn. Syst., 2018

A Spectral Approach for the Design of Experiments: Design, Analysis and Algorithms.
J. Mach. Learn. Res., 2018

Improved Community Detection using Deep Embeddings from Multilayer Graphs.
CoRR, 2018

MimicGAN: Corruption-Mimicking for Blind Image Recovery & Adversarial Defense.
CoRR, 2018

Improving Robustness of Attention Models on Graphs.
CoRR, 2018

Unsupervised Dimension Selection using a Blue Noise Spectrum.
CoRR, 2018

Attention Models with Random Features for Multi-layered Graph Embeddings.
CoRR, 2018

Can Deep Clinical Models Handle Real-World Domain Shifts?
CoRR, 2018

Controlled Random Search Improves Sample Mining and Hyper-Parameter Optimization.
CoRR, 2018

An Unsupervised Approach to Solving Inverse Problems using Generative Adversarial Networks.
CoRR, 2018

Exploring High-Dimensional Structure via Axis-Aligned Decomposition of Linear Projections.
Comput. Graph. Forum, 2018

Mitigating inter-job interference using adaptive flow-aware routing.
Proceedings of the International Conference for High Performance Computing, 2018

PADDLE: Performance Analysis Using a Data-Driven Learning Environment.
Proceedings of the 2018 IEEE International Parallel and Distributed Processing Symposium, 2018

Triplet Network with Attention for Speaker Diarization.
Proceedings of the 19th Annual Conference of the International Speech Communication Association, 2018

Bootstrapping Parameter Space Exploration for Fast Tuning.
Proceedings of the 32nd International Conference on Supercomputing, 2018

A Generative Modeling Approach to Limited Channel ECG Classification.
Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018

Lose the Views: Limited Angle CT Reconstruction via Implicit Sinogram Completion.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Attend and Diagnose: Clinical Time Series Analysis Using Attention Models.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Influential Sample Selection: A Graph Signal Processing Approach.
CoRR, 2017

Efficient Data-Driven Geologic Feature Detection from Pre-stack Seismic Measurements using Randomized Machine-Learning Algorithm.
CoRR, 2017

Performance modeling under resource constraints using deep transfer learning.
Proceedings of the International Conference for High Performance Computing, 2017

Learning Robust Representations for Computer Vision.
Proceedings of the 2017 IEEE International Conference on Computer Vision Workshops, 2017

A deep learning approach to multiple kernel fusion.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Poisson Disk Sampling on the Grassmannnian: Applications in Subspace Optimization.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2017

2016
Stair blue noise sampling.
ACM Trans. Graph., 2016

Universal Collaboration Strategies for Signal Detection: A Sparse Learning Approach.
IEEE Signal Process. Lett., 2016

TreeView: Peeking into Deep Neural Networks Via Feature-Space Partitioning.
CoRR, 2016

Data-Driven Performance Modeling of Linear Solvers for Sparse Matrices.
Proceedings of the 7th International Workshop on Performance Modeling, 2016

A machine learning framework for performance coverage analysis of proxy applications.
Proceedings of the International Conference for High Performance Computing, 2016

Sparsifying Word Representations for Deep Unordered Sentence Modeling.
Proceedings of the 1st Workshop on Representation Learning for NLP, 2016

Influential Node Detection in Implicit Social Networks using Multi-task Gaussian Copula Models.
Proceedings of the NIPS 2016 Time Series Workshop, 2016

Measuring glomerular number from kidney MRI images.
Proceedings of the Medical Imaging 2016: Image Processing, 2016

Lung nodule detection using 3D convolutional neural networks trained on weakly labeled data.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016

Auto-context modeling using multiple Kernel learning.
Proceedings of the 2016 IEEE International Conference on Image Processing, 2016

Robust Local Scaling Using Conditional Quantiles of Graph Similarities.
Proceedings of the IEEE International Conference on Data Mining Workshops, 2016

Consensus inference on mobile phone sensors for activity recognition.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Beyond L2-loss functions for learning sparse models.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Theoretical guarantees for poisson disk sampling using pair correlation function.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

2015
Learning Stable Multilevel Dictionaries for Sparse Representations.
IEEE Trans. Neural Networks Learn. Syst., 2015

Undergraduate Signal Processing Laboratories for the Android Operating System.
CoRR, 2015

Visual Exploration of High-Dimensional Data through Subspace Analysis and Dynamic Projections.
Comput. Graph. Forum, 2015

Identifying the Culprits Behind Network Congestion.
Proceedings of the 2015 IEEE International Parallel and Distributed Processing Symposium, 2015

A Randomized Ensemble Approach to Industrial CT Segmentation.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Subspace learning using consensus on the grassmannian manifold.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

2014
Image Understanding Using Sparse Representations
Synthesis Lectures on Image, Video, and Multimedia Processing, Morgan & Claypool Publishers, ISBN: 978-3-031-02250-0, 2014

Multiple Kernel Sparse Representations for Supervised and Unsupervised Learning.
IEEE Trans. Image Process., 2014

Kernel Sparse Models for Automated Tumor Segmentation.
Int. J. Artif. Intell. Tools, 2014

Recovering non-negative and combined sparse representations.
Digit. Signal Process., 2014

Computing persistent homology under random projection.
Proceedings of the IEEE Workshop on Statistical Signal Processing, 2014

Multivariate volume visualization through dynamic projections.
Proceedings of the 4th IEEE Symposium on Large Data Analysis and Visualization, 2014

Automatic image annotation using inverse maps from semantic embeddings.
Proceedings of the 2014 IEEE International Conference on Image Processing, 2014

Image segmentation using consensus from hierarchical segmentation ensembles.
Proceedings of the 2014 IEEE International Conference on Image Processing, 2014

Multiple kernel interpolation for inverting non-linear dimensionality reduction and dimension estimation.
Proceedings of the IEEE International Conference on Acoustics, 2014

A scalable feature learning and tag prediction framework for natural environment sounds.
Proceedings of the 48th Asilomar Conference on Signals, Systems and Computers, 2014

Consensus inference with multilayer graphs for multi-modal data.
Proceedings of the 48th Asilomar Conference on Signals, Systems and Computers, 2014

2013
Sparse Methods in Image Understanding and Computer Vision.
PhD thesis, 2013

Mixing matrix estimation using discriminative clustering for blind source separation.
Digit. Signal Process., 2013

Learning Stable Multilevel Dictionaries for Sparse Representation of Images
CoRR, 2013

Ensemble Sparse Models for Image Analysis
CoRR, 2013

Boosted dictionaries for image restoration based on sparse representations.
Proceedings of the IEEE International Conference on Acoustics, 2013

A heterogeneous dictionary model for representation and recognition of human actions.
Proceedings of the IEEE International Conference on Acoustics, 2013

2012
Learning Multilevel Dictionaries for Compressed Sensing Using Discriminative Clustering.
Proceedings of the Eighth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2012

Supervised local sparse coding of sub-image features for image retrieval.
Proceedings of the 19th IEEE International Conference on Image Processing, 2012

Interactive DSP laboratories on mobile phones and tablets.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

Work in progress: Performing signal analysis laboratories using Android devices.
Proceedings of the IEEE Frontiers in Education Conference, 2012

Implementation of a fast image coding and retrieval system using a GPU.
Proceedings of the 2012 IEEE International Conference on Emerging Signal Processing Applications, 2012

Automated tumor segmentation using kernel sparse representations.
Proceedings of the 12th IEEE International Conference on Bioinformatics & Bioengineering, 2012

Learning dictionaries with graph embedding constraints.
Proceedings of the Conference Record of the Forty Sixth Asilomar Conference on Signals, 2012

2011
Analysis of the MPEG-1 Layer III (MP3) Algorithm Using MATLAB
Synthesis Lectures on Algorithms and Software in Engineering, Morgan & Claypool Publishers, ISBN: 978-3-031-01518-2, 2011

Optimality and stability of the K-hyperline clustering algorithm.
Pattern Recognit. Lett., 2011

Transform domain features for ion-channel signal classification.
Biomed. Signal Process. Control., 2011

Improved sparse coding using manifold projections.
Proceedings of the 18th IEEE International Conference on Image Processing, 2011

Analyte detection using an ion-channel sensor array.
Proceedings of the 17th International Conference on Digital Signal Processing, 2011

Work in progress - Modules and laboratories for a pathways course in signals and systems.
Proceedings of the 2011 Frontiers in Education Conference, 2011

Work in progress - Interactive signal-processing labs and simulations on iOS devices.
Proceedings of the 2011 Frontiers in Education Conference, 2011

Learning dictionaries for local sparse coding in image classification.
Proceedings of the Conference Record of the Forty Fifth Asilomar Conference on Signals, 2011

2010
Dimensionality Reduction for Distance Based Video Clustering.
Proceedings of the Artificial Intelligence Applications and Innovations, 2010

2009
Template Learning using Wavelet Domain Statistical Models.
Proceedings of the Research and Development in Intelligent Systems XXVI, 2009

Fast image registration with non-stationary Gauss-Markov random field templates.
Proceedings of the International Conference on Image Processing, 2009

2008
Sparse Representations for Pattern Classification using Learned Dictionaries.
Proceedings of the Research and Development in Intelligent Systems XXV, 2008


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