Jayaraman J. Thiagarajan

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All published works

Action	Title	Year	Authors
+ PDF Chat	Leveraging Registers in Vision Transformers for Robust Adaptation	2025	Srikar Yellapragada Kowshik Thopalli Vivek Narayanaswamy Wesam Sakla Yang Liu Yamen Mubarka Dimitris Samaras Jayaraman J. Thiagarajan
+ PDF Chat	Physics-Informed Transformation Toward Improving the Machine-Learned NLTE Models of ICF Simulations	2024	Min Sang Cho Paul Grabowski Kowshik Thopalli T. S. Jayram Michael J. Barrow Jayaraman J. Thiagarajan Rushil Anirudh Hai Phuong Le H. A. Scott Joshua Kallman
+ PDF Chat	On The Role of Prompt Construction In Enhancing Efficacy and Efficiency of LLM-Based Tabular Data Generation	2024	Banooqa Banday Kowshik Thopalli Tanzima Islam Jayaraman J. Thiagarajan
+ PDF Chat	DECIDER: Leveraging Foundation Model Priors for Improved Model Failure Detection and Explanation	2024	Rakshith Subramanyam Kowshik Thopalli Vivek Narayanaswamy Jayaraman J. Thiagarajan
+ PDF Chat	Enhancing Accuracy and Parameter-Efficiency of Neural Representations for Network Parameterization	2024	Hongjun Choi Jayaraman J. Thiagarajan Ruben Glatt Shusen Liu
+ PDF Chat	Speeding Up Image Classifiers with Little Companions	2024	Yang Liu Kowshik Thopalli Jayaraman J. Thiagarajan
+ PDF Chat	On the Use of Anchoring for Training Vision Models	2024	Vivek Narayanaswamy Kowshik Thopalli Rushil Anirudh Yamen Mubarka Wesam Sakla Jayaraman J. Thiagarajan
+	Transformer-Powered Surrogates Close the ICF Simulation-Experiment Gap with Extremely Limited Data	2024	Matthew Olson Shusen Liu Jayaraman J. Thiagarajan Bogdan Kustowski Weng‐Keen Wong Rushil Anirudh
+ PDF Chat	`Eyes of a Hawk and Ears of a Fox': Part Prototype Network for Generalized Zero-Shot Learning	2024	Joshua Feinglass Jayaraman J. Thiagarajan Rushil Anirudh T. S. Jayram Yezhou Yang
+	Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks	2024	Puja Trivedi Mark Heimann Rushil Anirudh Danai Koutra Jayaraman J. Thiagarajan
+ PDF Chat	DOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstruction	2023	Jiaming Liu Rushil Anirudh Jayaraman J. Thiagarajan Stewart He Karthika Mohan Ulugbek S. Kamilov Hyo-Jin Kim
+ PDF Chat	Federated benchmarking of medical artificial intelligence with MedPerf	2023	Alexandros Karargyris Renato Umeton Micah Sheller Alejandro Aristizabal Johnu George Anna Wuest Sarthak Pati Hasan Kassem Maximilian Zenk Ujjwal Baid
+ PDF Chat	2022 Review of Data-Driven Plasma Science	2023	Rushil Anirudh Richard Archibald M. Salman Asif Markus M. Becker S. Benkadda Peer‐Timo Bremer Rick H. S. Budé C. S. Chang L. Chen R.M. Churchill
+ PDF Chat	Cross-GAN Auditing: Unsupervised Identification of Attribute Level Similarities and Differences Between Pretrained Generative Models	2023	Matthew Olson Shusen Liu Rushil Anirudh Jayaraman J. Thiagarajan Peer‐Timo Bremer W. Eric Wong
+ PDF Chat	Improving Diversity with Adversarially Learned Transformations for Domain Generalization	2023	Tejas Gokhale Rushil Anirudh Jayaraman J. Thiagarajan Bhavya Kailkhura Chitta Baral Yezhou Yang
+	Contrastive Knowledge-Augmented Meta-Learning for Few-Shot Classification	2023	Rakshith Subramanyam Mark Heimann T.S. Jayram Rushil Anirudh Jayaraman J. Thiagarajan
+	Cross-GAN Auditing: Unsupervised Identification of Attribute Level Similarities and Differences between Pretrained Generative Models	2023	Matthew Olson Shusen Liu Rushil Anirudh Jayaraman J. Thiagarajan Peer‐Timo Bremer W. Eric Wong
+	A Closer Look at Model Adaptation using Feature Distortion and Simplicity Bias	2023	Puja Trivedi Danai Koutra Jayaraman J. Thiagarajan
+	On the Efficacy of Generalization Error Prediction Scoring Functions	2023	Puja Trivedi Danai Koutra Jayaraman J. Thiagarajan
+	Target-Aware Generative Augmentations for Single-Shot Adaptation	2023	Kowshik Thopalli Rakshith Subramanyam Pavan Turaga Jayaraman J. Thiagarajan
+	CREPE: Learnable Prompting With CLIP Improves Visual Relationship Prediction	2023	Rakshith Subramanyam T. S. Jayram Rushil Anirudh Jayaraman J. Thiagarajan
+	Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks	2023	Puja Trivedi Mark Heimann Rushil Anirudh Danai Koutra Jayaraman J. Thiagarajan
+	PAGER: A Framework for Failure Analysis of Deep Regression Models	2023	Jayaraman J. Thiagarajan Vivek Narayanaswamy Puja Trivedi Rushil Anirudh
+	Transformer-Powered Surrogates Close the ICF Simulation-Experiment Gap with Extremely Limited Data	2023	Matthew Olson Shusen Liu Jayaraman J. Thiagarajan Bogdan Kustowski Weng‐Keen Wong Rushil Anirudh
+ PDF Chat	Single Model Uncertainty Estimation via Stochastic Data Centering	2022	Jayaraman J. Thiagarajan
+	Exploring the Design of Adaptation Protocols for Improved Generalization and Machine Learning Safety	2022	P Trivedi D Koutra Jayaraman J. Thiagarajan
+	Domain Alignment Meets Fully Test-Time Adaptation	2022	K Thopalli P Turaga Jayaraman J. Thiagarajan
+	Revisiting Inlier and Outlier Specification for Improved Out-of-Distribution Detection	2022	V Narayanaswamy Yamen Mubarka Rushil Anirudh D Rajan A Spanias Jayaraman J. Thiagarajan
+ PDF Chat	Enabling machine learning-ready HPC ensembles with Merlin	2022	J. L. Peterson Ben Bay J. M. Koning Peter Robinson Jessica Semler Jeremy White Rushil Anirudh Kevin Athey Peer‐Timo Bremer Francesco Di Natale
+	Revisiting Deep Subspace Alignment for Unsupervised Domain Adaptation	2022	Kowshik Thopalli Jayaraman J. Thiagarajan Rushil Anirudh Pavan Turaga
+	2022 Review of Data-Driven Plasma Science	2022	Rushil Anirudh Richard Archibald M. Salman Asif Markus M. Becker S. Benkadda Peer‐Timo Bremer Rick H. S. Budé C. S. Chang L. Chen R M Churchill
+	Improving Diversity with Adversarially Learned Transformations for Domain Generalization	2022	Tejas Gokhale Rushil Anirudh Jayaraman J. Thiagarajan Bhavya Kailkhura Chitta Baral Yezhou Yang
+	Domain Alignment Meets Fully Test-Time Adaptation	2022	Kowshik Thopalli Pavan Turaga Jayaraman J. Thiagarajan
+	Out of Distribution Detection via Neural Network Anchoring	2022	Rushil Anirudh Jayaraman J. Thiagarajan
+	Know Your Space: Inlier and Outlier Construction for Calibrating Medical OOD Detectors	2022	Vivek Narayanaswamy Yamen Mubarka Rushil Anirudh Deepta Rajan Andreas Spanias Jayaraman J. Thiagarajan
+	Single Model Uncertainty Estimation via Stochastic Data Centering	2022	Jayaraman J. Thiagarajan Rushil Anirudh Vivek Narayanaswamy Peer‐Timo Bremer
+	Contrastive Knowledge-Augmented Meta-Learning for Few-Shot Classification	2022	Rakshith Subramanyam Mark Heimann Jayram Thathachar Rushil Anirudh Jayaraman J. Thiagarajan
+	Exploring the Design of Adaptation Protocols for Improved Generalization and Machine Learning Safety	2022	Puja Trivedi Danai Koutra Jayaraman J. Thiagarajan
+	Analyzing Data-Centric Properties for Graph Contrastive Learning	2022	Puja Trivedi Ekdeep Singh Lubana Mark Heimann Danai Koutra Jayaraman J. Thiagarajan
+	Single-Shot Domain Adaptation via Target-Aware Generative Augmentation	2022	Rakshith Subramanyam Kowshik Thopalli Spring Berman Pavan Turaga Jayaraman J. Thiagarajan
+	On-the-fly Object Detection using StyleGAN with CLIP Guidance	2022	Yuzhe Lu Shusen Liu Jayaraman J. Thiagarajan Wesam Sakla Rushil Anirudh
+	DOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstruction	2022	Jiaming Liu Rushil Anirudh Jayaraman J. Thiagarajan Stewart He Karthika Mohan Ulugbek S. Kamilov Hyojin Kim
+	Geometric Priors for Scientific Generative Models in Inertial Confinement Fusion	2021	Ankita Shukla Rushil Anirudh Eugene Kur Jayaraman J. Thiagarajan Peer‐Timo Bremer B. K. Spears T. Ma Pavan Turaga
+	Δ-UQ: Accurate Uncertainty Quantification via Anchor Marginalization.	2021	Rushil Anirudh Jayaraman J. Thiagarajan
+	MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation.	2021	Alexandros Karargyris Renato Umeton Micah Sheller Alejandro Aristizabal Johnu George Srini Bala Daniel J. Beutel Victor Bittorf Akshay Chaudhari Alexander Chowdhury
+	On the Design of Deep Priors for Unsupervised Audio Restoration	2021	V Narayanaswamy Jayaraman J. Thiagarajan A Spanias
+	Designing Counterfactual Generators using Deep Model Inversion	2021	Jayaraman J. Thiagarajan Vivek Narayanaswamy Deepta Rajan Jason Liang Akshay Chaudhari Andreas Spanias
+ PDF Chat	Accurate and Robust Feature Importance Estimation under Distribution Shifts	2021	Jayaraman J. Thiagarajan Vivek Narayanaswamy Rushil Anirudh Peer‐Timo Bremer Andreas Spanias
+ PDF Chat	Uncertainty-Matching Graph Neural Networks to Defend Against Poisoning Attacks	2021	Uday Shankar Shanthamallu Jayaraman J. Thiagarajan Andreas Spanias
+ PDF Chat	Attribute-Guided Adversarial Training for Robustness to Natural Perturbations	2021	Tejas Gokhale Rushil Anirudh Bhavya Kailkhura Jayaraman J. Thiagarajan Chitta Baral Yezhou Yang
+	Accurate and Robust Feature Importance Estimation under Distribution Shifts.	2021	Jayaraman J. Thiagarajan Vivek Narayanaswamy Rushil Anirudh Peer‐Timo Bremer Andreas Spanias
+	Using Deep Image Priors to Generate Counterfactual Explanations	2021	Vivek Narayanaswamy Jayaraman J. Thiagarajan Andreas Spanias
+ PDF Chat	MARGIN: Uncovering Deep Neural Networks Using Graph Signal Analysis	2021	Rushil Anirudh Jayaraman J. Thiagarajan Rahul Sridhar Peer‐Timo Bremer
+	Transfer learning suppresses simulation bias in predictive models built from sparse, multi-modal data.	2021	Bogdan Kustowski Jim Gaffney B. K. Spears Gemma J. Anderson Rushil Anirudh Peer‐Timo Bremer Jayaraman J. Thiagarajan
+	On the Design of Deep Priors for Unsupervised Audio Restoration	2021	Vivek Narayanaswamy Jayaraman J. Thiagarajan Andreas Spanias
+	Loss Estimators Improve Model Generalization.	2021	Vivek Narayanaswamy Jayaraman J. Thiagarajan Deepta Rajan Andreas Spanias
+	Loss Estimators Improve Model Generalization	2021	V Narayanaswamy Jayaraman J. Thiagarajan D Rajan A Spanias
+ PDF Chat	Comparative Code Structure Analysis using Deep Learning for Performance Prediction	2021	Tarek Ramadan Tanzima Islam Chase Phelps Nathan Pinnow Jayaraman J. Thiagarajan
+	Self-training with improved regularization for sample-efficient chest x-ray classification	2021	Deepta Rajan Jayaraman J. Thiagarajan Alexandros Karargyris Satyananda Kashyap
+	Comparative Code Structure Analysis using Deep Learning for Performance Prediction	2021	Nathan Pinnow Tarek Ramadan Tanzima Islam Chase Phelps Jayaraman J. Thiagarajan
+	Automated Domain Discovery from Multiple Sources to Improve Zero-Shot Generalization	2021	Kowshik Thopalli Sameeksha Katoch Andreas Spanias Pavan Turaga Jayaraman J. Thiagarajan
+	Geometric Priors for Scientific Generative Models in Inertial Confinement Fusion	2021	Ankita Shukla Rushil Anirudh Eugene Kur Jayaraman J. Thiagarajan Peer‐Timo Bremer B. K. Spears T. Ma Pavan Turaga
+	$Δ$-UQ: Accurate Uncertainty Quantification via Anchor Marginalization	2021	Rushil Anirudh Jayaraman J. Thiagarajan
+	Designing Counterfactual Generators using Deep Model Inversion	2021	Jayaraman J. Thiagarajan Vivek Narayanaswamy Deepta Rajan Jason Liang Akshay Chaudhari Andreas Spanias
+	MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation	2021	Alexandros Karargyris Renato Umeton Micah Sheller Alejandro Aristizabal Johnu George Srini Bala Daniel J. Beutel Victor Bittorf Akshay Chaudhari Alexander Chowdhury
+	Suppressing simulation bias using multi-modal data	2021	Bogdan Kustowski Jim Gaffney B. K. Spears Gemma J. Anderson Rushil Anirudh Peer‐Timo Bremer Jayaraman J. Thiagarajan Michael Kruse R. Nora
+	On the Design of Deep Priors for Unsupervised Audio Restoration	2021	Vivek Narayanaswamy Jayaraman J. Thiagarajan Andreas Spanias
+	Comparative Code Structure Analysis using Deep Learning for Performance Prediction	2021	Nathan Pinnow Tarek A. Ramadan Tanzima Islam Chase Phelps Jayaraman J. Thiagarajan
+	Loss Estimators Improve Model Generalization	2021	Vivek Narayanaswamy Jayaraman J. Thiagarajan Deepta Rajan Andreas Spanias
+ PDF Chat	Designing accurate emulators for scientific processes using calibration-driven deep models	2020	Jayaraman J. Thiagarajan Bindya Venkatesh Rushil Anirudh Peer‐Timo Bremer Jim Gaffney Gemma J. Anderson B. K. Spears
+	Meaningful uncertainties from deep neural network surrogates of large-scale numerical simulations.	2020	Gemma J. Anderson Jim Gaffney B. K. Spears Peer‐Timo Bremer Rushil Anirudh Jayaraman J. Thiagarajan
+ PDF Chat	Unsupervised Audio Source Separation Using Generative Priors	2020	Vivek Narayanaswamy Jayaraman J. Thiagarajan Rushil Anirudh Andreas Spanias
+	Using Deep Image Priors to Generate Counterfactual Explanations	2020	Vivek Narayanaswamy Jayaraman J. Thiagarajan Andreas Spanias
+	Machine Learning-Powered Mitigation Policy Optimization in Epidemiological Models.	2020	Jayaraman J. Thiagarajan Peer‐Timo Bremer Rushil Anirudh Timothy C. Germann Sara Y. Del Valle Frederick H. Streitz
+	Accurate Calibration of Agent-based Epidemiological Models with Neural Network Surrogates.	2020	Rushil Anirudh Jayaraman J. Thiagarajan Peer‐Timo Bremer Timothy C. Germann Sara Y. Del Valle Frederick H. Streitz
+	Undergraduate Signal Processing Laboratories for the Android Operating System	2020	Suhas Ranganath Jayaraman J. Thiagarajan Karthikeyan Natesan Ramamurthy Shuang Hu Mahesh K. Banavar Andreas Spanias
+	Unsupervised Audio Source Separation using Generative Priors	2020	Vivek Narayanaswamy Jayaraman J. Thiagarajan Rushil Anirudh Andreas Spanias
+	Self-Training with Improved Regularization for Few-Shot Chest X-Ray Classification.	2020	Deepta Rajan Jayaraman J. Thiagarajan Alexandros Karargyris Satyananda Kashyap
+	Self-Training with Improved Regularization for Sample-Efficient Chest X-Ray Classification	2020	Deepta Rajan Jayaraman J. Thiagarajan Alexandros Karargyris Satyananda Kashyap
+ PDF Chat	Improved surrogates in inertial confinement fusion with manifold and cycle consistencies	2020	Rushil Anirudh Jayaraman J. Thiagarajan Peer‐Timo Bremer B. K. Spears
+ PDF Chat	Coverage-Based Designs Improve Sample Mining and Hyperparameter Optimization	2020	Gowtham Muniraju Bhavya Kailkhura Jayaraman J. Thiagarajan Peer‐Timo Bremer Cihan Tepedelenlioğlu Andreas Spanias
+ PDF Chat	Learn-By-Calibrating: Using Calibration As A Training Objective	2020	Jayaraman J. Thiagarajan Bindya Venkatesh Deepta Rajan
+ PDF Chat	A Regularized Attention Mechanism for Graph Attention Networks	2020	Uday Shankar Shanthamallu Jayaraman J. Thiagarajan Andreas Spanias
+ PDF Chat	Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors	2020	Jayaraman J. Thiagarajan Bindya Venkatesh Prasanna Sattigeri Peer‐Timo Bremer
+	MimicGAN: Robust Projection onto Image Manifolds with Corruption Mimicking	2020	Rushil Anirudh Jayaraman J. Thiagarajan Bhavya Kailkhura Peer‐Timo Bremer
+	Calibrate and Prune: Improving Reliability of Lottery Tickets Through Prediction Calibration	2020	Bindya Venkatesh Jayaraman J. Thiagarajan Kowshik Thopalli Prasanna Sattigeri
+	Calibrating Healthcare AI: Towards Reliable and Interpretable Deep Predictive Models	2020	Jayaraman J. Thiagarajan Prasanna Sattigeri Deepta Rajan Bindya Venkatesh
+	Ask-n-Learn: Active Learning via Reliable Gradient Representations for Image Classification	2020	Bindya Venkatesh Jayaraman J. Thiagarajan
+	Attribute-Guided Adversarial Training for Robustness to Natural Perturbations	2020	Tejas Gokhale Rushil Anirudh Bhavya Kailkhura Jayaraman J. Thiagarajan Chitta Baral Yezhou Yang
+	Meaningful uncertainties from deep neural network surrogates of large-scale numerical simulations	2020	Gemma J. Anderson Jim Gaffney B. K. Spears Peer‐Timo Bremer Rushil Anirudh Jayaraman J. Thiagarajan
+	Using Deep Image Priors to Generate Counterfactual Explanations	2020	Vivek Narayanaswamy Jayaraman J. Thiagarajan Andreas Spanias
+	Machine Learning-Powered Mitigation Policy Optimization in Epidemiological Models	2020	Jayaraman J. Thiagarajan Peer‐Timo Bremer Rushil Anirudh Timothy C. Germann Sara Y. Del Valle Frederick H. Streitz
+	Accurate Calibration of Agent-based Epidemiological Models with Neural Network Surrogates	2020	Rushil Anirudh Jayaraman J. Thiagarajan Peer‐Timo Bremer Timothy C. Germann Sara Y. Del Valle Frederick H. Streitz
+	Unsupervised Audio Source Separation using Generative Priors	2020	Vivek Narayanaswamy Jayaraman J. Thiagarajan Rushil Anirudh Andreas Spanias
+	Self-Training with Improved Regularization for Sample-Efficient Chest X-Ray Classification	2020	Deepta Rajan Jayaraman J. Thiagarajan Alexandros Karargyris Satyananda Kashyap
+	Uncertainty-Matching Graph Neural Networks to Defend Against Poisoning Attacks	2020	Uday Shankar Shanthamallu Jayaraman J. Thiagarajan Andreas Spanias
+	Accurate and Robust Feature Importance Estimation under Distribution Shifts	2020	Jayaraman J. Thiagarajan Vivek Narayanaswamy Rushil Anirudh Peer‐Timo Bremer Andreas Spanias
+	Improved Surrogates in Inertial Confinement Fusion with Manifold and Cycle Consistencies	2019	Rushil Anirudh Jayaraman J. Thiagarajan Peer‐Timo Bremer B. K. Spears
+	MimicGAN: Robust Projection onto Image Manifolds with Corruption Mimicking	2019	Rushil Anirudh Jayaraman J. Thiagarajan Bhavya Kailkhura Peer‐Timo Bremer
+	Merlin: Enabling Machine Learning-Ready HPC Ensembles	2019	J. L. Peterson Rushil Anirudh Kevin Athey Benjamin Bay Peer‐Timo Bremer Vic Castillo Francesco Di Natale David L. Fox Jim Gaffney David Hysom
+ PDF Chat	Distill-to-Label: Weakly Supervised Instance Labeling Using Knowledge Distillation	2019	Jayaraman J. Thiagarajan Satyananda Kashyap Alexandros Karargyris
+	Invenio: Discovering Hidden Relationships Between Tasks/Domains Using Structured Meta Learning	2019	Sameeksha Katoch Kowshik Thopalli Jayaraman J. Thiagarajan Pavan Turaga Andreas Spanias
+	GrAMME: Semisupervised Learning Using Multilayered Graph Attention Models	2019	Uday Shankar Shanthamallu Jayaraman J. Thiagarajan Huan Song Andreas Spanias
+	Learn-By-Calibrating: Using Calibration as a Training Objective	2019	Jayaraman J. Thiagarajan Bindya Venkatesh Deepta Rajan
+	Improving Limited Angle CT Reconstruction with a Robust GAN Prior	2019	Rushil Anirudh Hyojin Kim Jayaraman J. Thiagarajan Karthika Mohan Kyle Champley
+	Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors	2019	Jayaraman J. Thiagarajan Bindya Venkatesh Prasanna Sattigeri Peer‐Timo Bremer
+	Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications	2019	Shusen Liu Jim Gaffney Luc Peterson Peter Robinson Harsh Bhatia Valerio Pascucci B. K. Spears Peer‐Timo Bremer Di Wang Dan Maljovec
+	Distill-to-Label: Weakly Supervised Instance Labeling Using Knowledge Distillation	2019	Jayaraman J. Thiagarajan Satyananda Kashyap Alexandros Karagyris
+	Multiple Subspace Alignment Improves Domain Adaptation	2019	Kowshik Thopalli Rushil Anirudh Jayaraman J. Thiagarajan Pavan Turaga
+ PDF Chat	Designing an Effective Metric Learning Pipeline for Speaker Diarization	2019	Vivek Narayanaswamy Jayaraman J. Thiagarajan Huan Song Andreas Spanias
+	Understanding Deep Neural Networks through Input Uncertainties	2019	Jayaraman J. Thiagarajan Irene Kim Rushil Anirudh Peer‐Timo Bremer
+	Bootstrapping Graph Convolutional Neural Networks for Autism Spectrum Disorder Classification	2019	Rushil Anirudh Jayaraman J. Thiagarajan
+	Audio Source Separation via Multi-Scale Learning with Dilated Dense U-Nets	2019	Vivek Narayanaswamy Sameeksha Katoch Jayaraman J. Thiagarajan Huan Song Andreas Spanias
+	A Look at the Effect of Sample Design on Generalization through the Lens of Spectral Analysis	2019	Bhavya Kailkhura Jayaraman J. Thiagarajan Qunwei Li Peer‐Timo Bremer
+	SALT: Subspace Alignment as an Auxiliary Learning Task for Domain Adaptation	2019	Kowshik Thopalli Jayaraman J. Thiagarajan Rushil Anirudh Pavan Turaga
+	Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications	2019	Shusen Liu Di Wang Dan Maljovec Rushil Anirudh Jayaraman J. Thiagarajan Sam Adé Jacobs Brian C. Van Essen David Hysom Jae-Seung Yeom Jim Gaffney
+	Function Preserving Projection for Scalable Exploration of High-Dimensional Data	2019	Shusen Liu Rushil Anirudh Jayaraman J. Thiagarajan Peer‐Timo Bremer
+	Exploring Generative Physics Models with Scientific Priors in Inertial Confinement Fusion	2019	Rushil Anirudh Jayaraman J. Thiagarajan Shusen Liu Peer‐Timo Bremer B. K. Spears
+	Heteroscedastic Calibration of Uncertainty Estimators in Deep Learning	2019	Bindya Venkatesh Jayaraman J. Thiagarajan
+	Enabling Machine Learning-Ready HPC Ensembles with Merlin	2019	Peterson Jl Bay B J. M. Koning Peter Robinson Jessica Semler Jeremy White Rushil Anirudh Kevin Athey Peer‐Timo Bremer Natale Fd
+	MimicGAN: Robust Projection onto Image Manifolds with Corruption Mimicking	2019	Rushil Anirudh Jayaraman J. Thiagarajan Bhavya Kailkhura Peer‐Timo Bremer
+	Invenio: Discovering Hidden Relationships Between Tasks/Domains Using Structured Meta Learning	2019	Sameeksha Katoch Kowshik Thopalli Jayaraman J. Thiagarajan Pavan Turaga Andreas Spanias
+	Learn-By-Calibrating: Using Calibration as a Training Objective	2019	Jayaraman J. Thiagarajan Bindya Venkatesh Deepta Rajan
+	Improving Limited Angle CT Reconstruction with a Robust GAN Prior	2019	Rushil Anirudh Hyojin Kim Jayaraman J. Thiagarajan K. Aditya Mohan Kyle Champley
+	Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors	2019	Jayaraman J. Thiagarajan Bindya Venkatesh Prasanna Sattigeri Peer‐Timo Bremer
+	Distill-to-Label: Weakly Supervised Instance Labeling Using Knowledge Distillation	2019	Jayaraman J. Thiagarajan Satyananda Kashyap Alexandros Karagyris
+	Audio Source Separation via Multi-Scale Learning with Dilated Dense U-Nets	2019	Vivek Narayanaswamy Sameeksha Katoch Jayaraman J. Thiagarajan Huan Song Andreas Spanias
+	MimicGAN: Corruption-Mimicking for Blind Image Recovery & Adversarial Defense	2018	Rushil Anirudh Jayaraman J. Thiagarajan Bhavya Kailkhura Peer‐Timo Bremer
+	Designing an Effective Metric Learning Pipeline for Speaker Diarization	2018	Vivek Narayanaswamy Jayaraman J. Thiagarajan Huan Song Andreas Spanias
+	Improving Robustness of Attention Models on Graphs.	2018	Uday Shankar Shanthamallu Jayaraman J. Thiagarajan Andreas Spanias
+	A Regularized Attention Mechanism for Graph Attention Networks.	2018	Uday Shankar Shanthamallu Jayaraman J. Thiagarajan Andreas Spanias
+	Understanding Deep Neural Networks through Input Uncertainties	2018	Jayaraman J. Thiagarajan Irene Kim Rushil Anirudh Peer‐Timo Bremer
+	Attention Models with Random Features for Multi-layered Graph Embeddings.	2018	Uday Shankar Shanthamallu Jayaraman J. Thiagarajan Huan Song Andreas Spanias
+	GrAMME: Semi-Supervised Learning using Multi-layered Graph Attention Models	2018	Uday Shankar Shanthamallu Jayaraman J. Thiagarajan Huan Song Andreas Spanias
+	Can Deep Clinical Models Handle Real-World Domain Shifts?	2018	Jayaraman J. Thiagarajan Deepta Rajan Prasanna Sattigeri
+ PDF Chat	Efficient Data-Driven Geologic Feature Characterization from Pre-stack Seismic Measurements using Randomized Machine-Learning Algorithm	2018	Youzuo Lin Shusen Wang Jayaraman J. Thiagarajan George D. Guthrie David Coblentz
+	Controlled Random Search Improves Hyper-Parameter Optimization	2018	Gowtham Muniraju Bhavya Kailkhura Jayaraman J. Thiagarajan Peer‐Timo Bremer
+	Coverage-Based Designs Improve Sample Mining and Hyper-Parameter Optimization	2018	Gowtham Muniraju Bhavya Kailkhura Jayaraman J. Thiagarajan Peer‐Timo Bremer Cihan Tepedelenlioğlu Andreas Spanias
+	Triplet Network with Attention for Speaker Diarization	2018	Huan Song Megan Willi Jayaraman J. Thiagarajan Visar Berisha Andreas Spanias
+ PDF Chat	Deep learning: A guide for practitioners in the physical sciences	2018	B. K. Spears James M. Brase Peer‐Timo Bremer Barry Chen J. E. Field Jim Gaffney Michael Kruse S. Langer Katie L. Lewis R. Nora
+ PDF Chat	A Generative Modeling Approach to Limited Channel ECG Classification	2018	Deepta Rajan Jayaraman J. Thiagarajan
+ PDF Chat	Exploring High‐Dimensional Structure via Axis‐Aligned Decomposition of Linear Projections	2018	Jayaraman J. Thiagarajan S. Liu Karthikeyan Natesan Ramamurthy Peer‐Timo Bremer
+ PDF Chat	Lose the Views: Limited Angle CT Reconstruction via Implicit Sinogram Completion	2018	Rushil Anirudh Hyojin Kim Jayaraman J. Thiagarajan K. Aditya Mohan Kyle Champley Peer‐Timo Bremer
+	An Unsupervised Approach to Solving Inverse Problems using Generative Adversarial Networks	2018	Rushil Anirudh Jayaraman J. Thiagarajan Bhavya Kailkhura Peer‐Timo Bremer
+ PDF Chat	Attend and Diagnose: Clinical Time Series Analysis Using Attention Models	2018	Huan Song Deepta Rajan Jayaraman J. Thiagarajan Andreas Spanias
+	Optimizing Kernel Machines Using Deep Learning	2018	Huan Song Jayaraman J. Thiagarajan Prasanna Sattigeri Andreas Spanias
+	A Generative Modeling Approach to Limited Channel ECG Classification	2018	Deepta Rajan Jayaraman J. Thiagarajan
+	MARGIN: Uncovering Deep Neural Networks using Graph Signal Analysis	2018	Rushil Anirudh Jayaraman J. Thiagarajan Rahul Sridhar Peer‐Timo Bremer
+	Unsupervised Dimension Selection using a Blue Noise Spectrum	2018	Jayaraman J. Thiagarajan Rushil Anirudh Rahul Sridhar Peer‐Timo Bremer
+	Improved Deep Embeddings for Inferencing with Multi-Layered Networks	2018	Huan Song Jayaraman J. Thiagarajan
+	Triplet Network with Attention for Speaker Diarization	2018	Huan Song Megan Willi Jayaraman J. Thiagarajan Visar Berisha Andreas Spanias
+	Understanding Behavior of Clinical Models under Domain Shifts	2018	Jayaraman J. Thiagarajan Deepta Rajan Prasanna Sattigeri
+	Multiple Subspace Alignment Improves Domain Adaptation	2018	Kowshik Thopalli Rushil Anirudh Jayaraman J. Thiagarajan Pavan Turaga
+	A Regularized Attention Mechanism for Graph Attention Networks	2018	Uday Shankar Shanthamallu Jayaraman J. Thiagarajan Andreas Spanias
+	Understanding Deep Neural Networks through Input Uncertainties	2018	Jayaraman J. Thiagarajan Irene Kim Rushil Anirudh Peer‐Timo Bremer
+	Designing an Effective Metric Learning Pipeline for Speaker Diarization	2018	Vivek Narayanaswamy Jayaraman J. Thiagarajan Huan Song Andreas Spanias
+	GrAMME: Semi-Supervised Learning using Multi-layered Graph Attention Models	2018	Uday Shankar Shanthamallu Jayaraman J. Thiagarajan Huan Song Andreas Spanias
+	Coverage-Based Designs Improve Sample Mining and Hyper-Parameter Optimization	2018	Gowtham Muniraju Bhavya Kailkhura Jayaraman J. Thiagarajan Peer‐Timo Bremer Cihan Tepedelenlioglu Andreas Spanias
+	An Unsupervised Approach to Solving Inverse Problems using Generative Adversarial Networks	2018	Rushil Anirudh Jayaraman J. Thiagarajan Bhavya Kailkhura Peer‐Timo Bremer
+	A Generative Modeling Approach to Limited Channel ECG Classification	2018	Deepta Rajan Jayaraman J. Thiagarajan
+	MimicGAN: Corruption-Mimicking for Blind Image Recovery & Adversarial Defense	2018	Rushil Anirudh Jayaraman J. Thiagarajan Bhavya Kailkhura Peer‐Timo Bremer
+	Exploring High-Dimensional Structure via Axis-Aligned Decomposition of Linear Projections	2017	Jayaraman J. Thiagarajan Shusen Liu Karthikeyan Natesan Ramamurthy Peer‐Timo Bremer
+	Lose The Views: Limited Angle CT Reconstruction via Implicit Sinogram Completion	2017	Rushil Anirudh Hyojin Kim Jayaraman J. Thiagarajan K. Aditya Mohan Kyle Champley Peer‐Timo Bremer
+	Influential Sample Selection: A Graph Signal Processing Approach.	2017	Rushil Anirudh Jayaraman J. Thiagarajan Rahul Sridhar Peer‐Timo Bremer
+ PDF Chat	Learning Robust Representations for Computer Vision	2017	Peng Zheng Aleksandr Y. Aravkin Jayaraman J. Thiagarajan Karthikeyan Natesan Ramamurthy
+	Bootstrapping Graph Convolutional Neural Networks for Autism Spectrum Disorder Classification	2017	Rushil Anirudh Jayaraman J. Thiagarajan
+ PDF Chat	A deep learning approach to multiple kernel fusion	2017	Huan Song Jayaraman J. Thiagarajan Prasanna Sattigeri Karthikeyan Natesan Ramamurthy Andreas Spanias
+	Data-Driven Metric Learning for History Matching	2017	Jacob Miller Jayaraman J. Thiagarajan Peer‐Timo Bremer Nazish Hoda Dave Stern Rick T. Mifflin
+	Learning Robust Representations for Computer Vision	2017	Peng Zheng Aleksandr Y. Aravkin Karthikeyan Natesan Ramamurthy Jayaraman J. Thiagarajan
+	Attend and Diagnose: Clinical Time Series Analysis using Attention Models	2017	Huan Song Deepta Rajan Jayaraman J. Thiagarajan Andreas Spanias
+	Optimizing Kernel Machines using Deep Learning	2017	Huan Song Jayaraman J. Thiagarajan Prasanna Sattigeri Andreas Spanias
+	A Spectral Approach for the Design of Experiments: Design, Analysis and Algorithms	2017	Bhavya Kailkhura Jayaraman J. Thiagarajan Charvi Rastogi Pramod K. Varshney Peer‐Timo Bremer
+	MARGIN: Uncovering Deep Neural Networks using Graph Signal Analysis	2017	Rushil Anirudh Jayaraman J. Thiagarajan Rahul Sridhar Peer‐Timo Bremer
+	Exploring High-Dimensional Structure via Axis-Aligned Decomposition of Linear Projections	2017	Jayaraman J. Thiagarajan Shusen Liu Karthikeyan Natesan Ramamurthy Peer‐Timo Bremer
+	Lose The Views: Limited Angle CT Reconstruction via Implicit Sinogram Completion	2017	Rushil Anirudh Hyojin Kim Jayaraman J. Thiagarajan Karthika Mohan Kyle Champley Peer‐Timo Bremer
+	Bootstrapping Graph Convolutional Neural Networks for Autism Spectrum Disorder Classification	2017	Rushil Anirudh Jayaraman J. Thiagarajan
+	Robust Local Scaling using Conditional Quantiles of Graph Similarities	2016	Jayaraman J. Thiagarajan Prasanna Sattigeri Karthikeyan Natesan Ramamurthy Bhavya Kailkhura
+	Robust Local Scaling Using Conditional Quantiles of Graph Similarities	2016	Jayaraman J. Thiagarajan Prasanna Sattigeri Karthikeyan Natesan Ramamurthy Bhavya Kailkhura
+	Autism Spectrum Disorder Classification using Graph Kernels on Multidimensional Time Series	2016	Rushil Anirudh Jayaraman J. Thiagarajan I Kim Wolfgang Polonik
+	Data-driven performance modeling of linear solvers for sparse matrices	2016	Jae-Seung Yeom Jayaraman J. Thiagarajan Abhinav Bhatelé Greg Bronevetsky Tzanio Kolev
+	Data-Driven Performance Modeling of Linear Solvers for Sparse Matrices	2016	J Yeom Jayaraman J. Thiagarajan Abhinav Bhatelé G Bronevetsky Tzanio Kolev
+ PDF Chat	Universal Collaboration Strategies for Signal Detection: A Sparse Learning Approach	2016	Prashant Khanduri Bhavya Kailkhura Jayaraman J. Thiagarajan Pramod K. Varshney
+	Beyond L2-loss functions for learning sparse models	2016	Karthikeyan Natesan Ramamurthy Aleksandr Y. Aravkin Jayaraman J. Thiagarajan
+	TreeView: Peeking into Deep Neural Networks Via Feature-Space Partitioning	2016	Jayaraman J. Thiagarajan Bhavya Kailkhura Prasanna Sattigeri Karthikeyan Natesan Ramamurthy
+	A Deep Learning Approach To Multiple Kernel Fusion	2016	Huan Song Jayaraman J. Thiagarajan Prasanna Sattigeri Karthikeyan Natesan Ramamurthy Andreas Spanias
+	Influential Node Detection in Implicit Social Networks using Multi-task Gaussian Copula Models	2016	Qunwei Li Bhavya Kailkhura Jayaraman J. Thiagarajan Zhenliang Zhang Pramod K. Varshney
+	Autism Spectrum Disorder Classification using Graph Kernels on Multidimensional Time Series	2016	Rushil Anirudh Jayaraman J. Thiagarajan Irene Kim Wolfgang Polonik
+	Robust Local Scaling using Conditional Quantiles of Graph Similarities	2016	Jayaraman J. Thiagarajan Prasanna Sattigeri Karthikeyan Natesan Ramamurthy Bhavya Kailkhura
+	Automatic Inference of the Quantile Parameter	2015	Karthikeyan Natesan Ramamurthy Aleksandr Y. Aravkin Jayaraman J. Thiagarajan
+	Automatic Inference of the Quantile Parameter	2015	Karthikeyan Natesan Ramamurthy Aleksandr Y. Aravkin Jayaraman J. Thiagarajan
+ PDF Chat	Learning Stable Multilevel Dictionaries for Sparse Representations	2014	Jayaraman J. Thiagarajan Karthikeyan Natesan Ramamurthy Andreas Spanias
+ PDF Chat	Kernel Sparse Models for Automated Tumor Segmentation	2014	Jayaraman J. Thiagarajan Karthikeyan Natesan Ramamurthy Deepta Rajan Andreas Spanias Anup Puri David Frakes
+ PDF Chat	Multiple Kernel Sparse Representations for Supervised and Unsupervised Learning	2014	Jayaraman J. Thiagarajan Karthikeyan Natesan Ramamurthy Andreas Spanias
+	Beyond L2-Loss Functions for Learning Sparse Models	2014	Karthikeyan Natesan Ramamurthy Aleksandr Y. Aravkin Jayaraman J. Thiagarajan
+	Beyond L2-Loss Functions for Learning Sparse Models	2014	Karthikeyan Natesan Ramamurthy Aleksandr Y. Aravkin Jayaraman J. Thiagarajan
+ PDF Chat	Recovering non-negative and combined sparse representations	2013	Karthikeyan Natesan Ramamurthy Jayaraman J. Thiagarajan Andreas Spanias
+	Recovering Non-negative and Combined Sparse Representations	2013	Karthikeyan Natesan Ramamurthy Jayaraman J. Thiagarajan Andreas Spanias
+	Learning Stable Multilevel Dictionaries for Sparse Representations	2013	Jayaraman J. Thiagarajan Karthikeyan Natesan Ramamurthy Andreas Spanias
+	Ensemble Sparse Models for Image Analysis	2013	Karthikeyan Natesan Ramamurthy Jayaraman J. Thiagarajan Prasanna Sattigeri Andreas Spanias
+	Recovering Non-negative and Combined Sparse Representations	2013	Karthikeyan Natesan Ramamurthy Jayaraman J. Thiagarajan Andreas Spanias
+	Kernel Sparse Models for Automated Tumor Segmentation	2013	Jayaraman J. Thiagarajan Karthikeyan Natesan Ramamurthy Deepta Rajan Anup Puri David Frakes Andreas Spanias
+	Learning Stable Multilevel Dictionaries for Sparse Representations	2013	Jayaraman J. Thiagarajan Karthikeyan Natesan Ramamurthy Andreas Spanias

Common Coauthors

Coauthor	Papers Together
Rushil Anirudh	83
Peer‐Timo Bremer	61
Andreas Spanias	56
Karthikeyan Natesan Ramamurthy	27
Vivek Narayanaswamy	26
Bhavya Kailkhura	26
Deepta Rajan	22
Huan Song	18
B. K. Spears	18
Kowshik Thopalli	17
Prasanna Sattigeri	16
Jim Gaffney	13
Shusen Liu	12
Pavan Turaga	12
Bindya Venkatesh	11
Satyananda Kashyap	10
Uday Shankar Shanthamallu	10
Bogdan Kustowski	9
Alexandros Karargyris	8
Aleksandr Y. Aravkin	7
Puja Trivedi	7
Danai Koutra	6
Rakshith Subramanyam	6
Sameeksha Katoch	5
Jae-Seung Yeom	5
Brian Van Essen	5
Peter Robinson	5
J. L. Peterson	5
Gemma J. Anderson	5
Kyle Champley	5
Rahul Sridhar	5
Mark Heimann	5
Akshay Chaudhari	5
Timothy C. Germann	4
Hyojin Kim	4
Sara Y. Del Valle	4
Irene Kim	4
Tanzima Islam	4
Gowtham Muniraju	4
Yezhou Yang	4
Sam Adé Jacobs	4
T. Ma	4
Chitta Baral	4
Tejas Gokhale	4
Karthika Mohan	4
Yamen Mubarka	4
Matthew Olson	4
Frederick H. Streitz	4
Peter Mattson	3
Gregory Diamos	3

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	Deep Residual Learning for Image Recognition	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	16
+ PDF Chat	Improved surrogates in inertial confinement fusion with manifold and cycle consistencies	2020	Rushil Anirudh Jayaraman J. Thiagarajan Peer‐Timo Bremer B. K. Spears	10
+	Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning	2015	Yarin Gal Zoubin Ghahramani	10
+	Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering	2016	Michaël Defferrard Xavier Bresson Pierre Vandergheynst	10
+ PDF Chat	Semantic Image Inpainting with Deep Generative Models	2017	Raymond A. Yeh Chen Chen Teck Yian Lim Alexander G. Schwing Mark Hasegawa–Johnson N. Minh	9
+ PDF Chat	Solving Linear Inverse Problems Using Gan Priors: An Algorithm with Provable Guarantees	2018	Viraj Shah Chinmay Hegde	9
+	Semi-Supervised Classification with Graph Convolutional Networks	2016	Thomas Kipf Max Welling	8
+	Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning	2015	Yarin Gal Zoubin Ghahramani	7
+	Deep Convolutional Networks on Graph-Structured Data	2015	Mikael Henaff Joan Bruna Yann LeCun	7
+ PDF Chat	Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network	2017	Christian Ledig Lucas Theis Ferenc Huszár José Caballero Andrew Cunningham Alejandro Acosta Andrew P. Aitken Alykhan Tejani Johannes Totz Zehan Wang	7
+	Semi-Supervised Classification with Graph Convolutional Networks	2016	Thomas Kipf Max Welling	7
+ PDF Chat	Learning for Single-Shot Confidence Calibration in Deep Neural Networks Through Stochastic Inferences	2019	Seonguk Seo Paul Hongsuck Seo Bohyung Han	7
+	On Calibration of Modern Neural Networks	2017	Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger	6
+	TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems	2016	Martı́n Abadi Ashish Agarwal Paul Barham Eugene Brevdo Zhifeng Chen Craig Citro Gregory S. Corrado Andy Davis Jay B. Dean Matthieu Devin	6
+	Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms	2017	Xiao Han Kashif Rasul Roland Vollgraf	6
+ PDF Chat	Least angle regression	2004	Bradley Efron Trevor Hastie Iain M. Johnstone Robert Tibshirani	6
+ PDF Chat	Uncertainties in Parameters Estimated with Neural Networks: Application to Strong Gravitational Lensing	2017	Laurence Perreault-Levasseur Yashar Hezaveh Risa H. Wechsler	6
+	Convolutional Networks on Graphs for Learning Molecular Fingerprints	2015	David Duvenaud Dougal Maclaurin Jorge Aguilera‐Iparraguirre Rafael Gómez‐Bombarelli Timothy Hirzel Alán Aspuru‐Guzik Ryan P. Adams	6
+	Accurate Uncertainties for Deep Learning Using Calibrated Regression	2018	Volodymyr Kuleshov Nathan Fenner Stefano Ermon	6
+ PDF Chat	ImageNet Large Scale Visual Recognition Challenge	2015	Olga Russakovsky Jia Deng Hao Su Jonathan Krause Sanjeev Satheesh Sean Ma Zhiheng Huang Andrej Karpathy Aditya Khosla Michael S. Bernstein	6
+	Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles	2016	Balaji Lakshminarayanan Alexander Pritzel Charles Blundell	6
+	Explaining and Harnessing Adversarial Examples	2014	Ian Goodfellow Jonathon Shlens Christian Szegedy	6
+	Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks	2015	Alec Radford Luke Metz Soumith Chintala	5
+ PDF Chat	Deep Learning Face Attributes in the Wild	2015	Ziwei Liu Ping Luo Xiaogang Wang Xiaoou Tang	5
+ PDF Chat	Towards Evaluating the Robustness of Neural Networks	2017	Nicholas Carlini David Wagner	5
+	Attention is All you Need	2017	Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N. Gomez Łukasz Kaiser Illia Polosukhin	5
+ PDF Chat	CaloGAN: Simulating 3D high energy particle showers in multilayer electromagnetic calorimeters with generative adversarial networks	2018	M. Paganini Luke de Oliveira Benjamin Nachman	5
+	Attention Is All You Need	2017	Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N. Gomez Łukasz Kaiser Illia Polosukhin	5
+ PDF Chat	Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization	2017	Ramprasaath R. Selvaraju Michael Cogswell Abhishek Das Ramakrishna Vedantam Devi Parikh Dhruv Batra	5
+ PDF Chat	DeepWalk	2014	Bryan Perozzi Rami Al‐Rfou Steven Skiena	5
+ PDF Chat	Learning Loss for Active Learning	2019	Donggeun Yoo In So Kweon	5
+	Weight Uncertainty in Neural Networks	2015	Charles Blundell Julien Cornebise Koray Kavukcuoglu Daan Wierstra	5
+ PDF Chat	Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks	2017	Jun-Yan Zhu Taesung Park Phillip Isola Alexei A. Efros	5
+	A Unified Approach to Interpreting Model Predictions	2017	Scott Lundberg Su‐In Lee	5
+	Spectral Networks and Locally Connected Networks on Graphs	2013	Joan Bruna Wojciech Zaremba Arthur Szlam Yann LeCun	5
+	Adam: A Method for Stochastic Optimization	2014	Diederik P. Kingma Jimmy Ba	5
+ PDF Chat	The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains	2013	David I Shuman Sunil K. Narang Pascal Frossard Antonio Ortega Pierre Vandergheynst	5
+ PDF Chat	Image-to-Image Translation with Conditional Adversarial Networks	2017	Phillip Isola Jun-Yan Zhu Tinghui Zhou Alexei A. Efros	5
+	What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?	2017	Alex Kendall Yarin Gal	5
+	Searching for exotic particles in high-energy physics with deep learning	2014	Pierre Baldi Peter Sadowski D. Whiteson	5
+	Wasserstein Auto-Encoders	2018	Ilya Tolstikhin Olivier Bousquet Sylvain Gelly Bernhard Schölkopf	4
+	Monte Carlo and Quasi-Monte Carlo for Statistics	2009	Art B. Owen	4
+	Distilling the Knowledge in a Neural Network	2015	Geoffrey E. Hinton Oriol Vinyals Jay B. Dean	4
+	Methods for interpreting and understanding deep neural networks	2017	Grégoire Montavon Wojciech Samek Klaus‐Robert Müller	4
+	Learning Important Features Through Propagating Activation Differences	2017	Avanti Shrikumar Peyton Greenside Anshul Kundaje	4
+ PDF Chat	Attend and Diagnose: Clinical Time Series Analysis Using Attention Models	2018	Huan Song Deepta Rajan Jayaraman J. Thiagarajan Andreas Spanias	4
+	Graph Attention Networks	2018	Petar Veličković Guillem Cucurull Arantxa Casanova Adriana Romero Píetro Lió Yoshua Bengio	4
+	Orthogonal Matching Pursuit for Sparse Quantile Regression	2014	Aleksandr Y. Aravkin Aurélie Lozano Ronny Luss Prabhajan Kambadur	4
+	Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps	2013	Karen Simonyan Andrea Vedaldi Andrew Zisserman	4
+	Shape Distributions of Nonlinear Dynamical Systems for Video-Based Inference	2016	Vinay Venkataraman Pavan Turaga	4