Peer‐Timo Bremer

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All published works

Action	Title	Year	Authors
+ 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	Bimodal Visualization of Industrial X-Ray and Neutron Computed Tomography Data	2024	Xuan Huang Haichao Miao Hyo-Jin Kim Andrew Townsend Kyle Champley Joseph W. Tringe Valerio Pascucci Peer‐Timo Bremer
+ PDF Chat	HPAC-ML: A Programming Model for Embedding ML Surrogates in Scientific Applications	2024	Zane Fink Konstantinos Parasyris Praneet Rathi Giorgis Georgakoudis Harshitha Menon Peer‐Timo Bremer
+ PDF Chat	Enabling Additive Manufacturing Part Inspection of Digital Twins via Collaborative Virtual Reality	2024	Vuthea Chheang Saurabh Narain Garrett Hooten Robert Cerda Brian Au Brian Thomas Weston Brian Giera Peer‐Timo Bremer Haichao Miao
+	A Virtual Environment for Collaborative Inspection in Additive Manufacturing	2024	Vuthea Chheang Brian Thomas Weston Robert Cerda Brian Au Brian Giera Peer‐Timo Bremer Haichao Miao
+ PDF Chat	A Virtual Environment for Collaborative Inspection in Additive Manufacturing	2024	Vuthea Chheang Brian Thomas Weston Robert Cerda Brian Au Brian Giera Peer‐Timo Bremer Haichao Miao
+ PDF Chat	“Understanding Robustness Lottery”: A Geometric Visual Comparative Analysis of Neural Network Pruning Approaches	2024	Zhimin Li Shusen Liu Xin Yu Bhavya Kailkhura Jie Cao James Diffenderfer Peer‐Timo Bremer Valerio Pascucci
+ 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
+	Workflows Community Summit 2022: A Roadmap Revolution	2023	Rafael Ferreira da Silva Rosa M. Badía Venkat Bala Deborah Bard Peer‐Timo Bremer Ian K. Buckley Silvina Caíno‐Lores Kyle Chard Carole Goble Shantenu Jha
+	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
+	Workflows Community Summit 2022: A Roadmap Revolution	2023	Rafael Ferreira da Silva Rosa M. Badía Venkat Bala Debbie Bard Peer‐Timo Bremer Ian K. Buckley Silvina Caíno‐Lores Kyle Chard Carole Goble Shantenu Jha
+	Instance-wise Linearization of Neural Network for Model Interpretation	2023	Zhimin Li Shusen Liu Bhavya Kailkhura Peer‐Timo Bremer Valerio Pascucci
+	Accelerating Flow Simulations using Online Dynamic Mode Decomposition	2023	Seung Won Suh Seung Whan Chung Peer‐Timo Bremer Young‐Soo Choi
+	AVA: Towards Autonomous Visualization Agents through Visual Perception-Driven Decision-Making	2023	Shusen Liu Haichao Miao Zhimin Li Matthew Olson Valerio Pascucci Peer‐Timo Bremer
+ PDF Chat	Data-driven model for divertor plasma detachment prediction	2022	Ben Zhu Menglong Zhao Harsh Bhatia X. Q. Xu Peer‐Timo Bremer William H. Meyer Nami Li Thomas D. Rognlien
+ PDF Chat	AMM: Adaptive Multilinear Meshes	2022	Harsh Bhatia Duong Hoang Nate Morrical Valerio Pascucci Peer‐Timo Bremer Peter Lindström
+ 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
+	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
+	"Understanding Robustness Lottery": A Geometric Visual Comparative Analysis of Neural Network Pruning Approaches	2022	Zhimin Li Shusen Liu Xin Yu Bhavya Kailkhura Jie Cao Diffenderfer James Daniel Peer‐Timo Bremer Valerio Pascucci
+	Data-driven model for divertor plasma detachment prediction	2022	Ben Zhu Menglong Zhao Harsh Bhatia X. Q. Xu Peer‐Timo Bremer William H. Meyer Nami Li T.D. Rognlien
+	Emerging Patterns in the Continuum Representation of Protein-Lipid Fingerprints	2022	Konstantia Georgouli Helgi I. Ingólfsson Fikret Aydin Mark Heimann Felice C. Lightstone Peer‐Timo Bremer Harsh Bhatia
+	Models Out of Line: A Fourier Lens on Distribution Shift Robustness	2022	Sara Fridovich-Keil Brian R. Bartoldson James Diffenderfer Bhavya Kailkhura Peer‐Timo Bremer
+	Identifying Orientation-specific Lipid-protein Fingerprints using Deep Learning	2022	Fikret Aydin Konstantia Georgouli Gautham Dharuman James N. Glosli Felice C. Lightstone Helgi I. Ingólfsson Peer‐Timo Bremer Harsh Bhatia
+	Single Model Uncertainty Estimation via Stochastic Data Centering	2022	Jayaraman J. Thiagarajan Rushil Anirudh Vivek Narayanaswamy Peer‐Timo Bremer
+	Towards replacing physical testing of granular materials with a Topology-based Model	2021	Aniketh Venkat Attila Gyulassy Graham Kosiba Amitesh Maiti Henry Reinstein Richard H. Gee Peer‐Timo Bremer Valerio Pascucci
+	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
+	Scalable Comparative Visualization of Ensembles of Call Graphs	2021	Suraj P. Kesavan Harsh Bhatia Abhinav Bhatelé Stephanie Brink Olga Pearce Todd Gamblin Peer‐Timo Bremer Kwan‐Liu Ma
+ PDF Chat	Accurate and Robust Feature Importance Estimation under Distribution Shifts	2021	Jayaraman J. Thiagarajan Vivek Narayanaswamy Rushil Anirudh Peer‐Timo Bremer Andreas Spanias
+	Accurate and Robust Feature Importance Estimation under Distribution Shifts.	2021	Jayaraman J. Thiagarajan Vivek Narayanaswamy Rushil Anirudh Peer‐Timo Bremer 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
+	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
+	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
+	Towards replacing physical testing of granular materials with a Topology-based Model	2021	Aniketh Venkat Attila Gyulassy Graham Kosiba Amitesh Maiti Henry Reinstein Richard H. Gee Peer‐Timo Bremer Valerio Pascucci
+ 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
+	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
+ 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	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
+	Scalable Comparative Visualization of Ensembles of Call Graphs	2020	Suraj P. Kesavan Harsh Bhatia Abhinav Bhatelé Todd Gamblin Peer‐Timo Bremer Kwan‐Liu Ma
+	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
+	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
+	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
+	Parallelizing Training of Deep Generative Models on Massive Scientific Datasets	2019	Sam Adé Jacobs Brian Van Essen David Hysom Jae-Seung Yeom Tim Moon Rushil Anirudh Jayaraman J. Thiagaranjan Shusen Liu Peer‐Timo Bremer Jim Gaffney
+	Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors	2019	Jayaraman J. Thiagarajan Bindya Venkatesh Prasanna Sattigeri Peer‐Timo Bremer
+	Parallelizing Training of Deep Generative Models on Massive Scientific Datasets	2019	Sam Adé Jacobs Jim Gaffney Tom Benson Peter Robinson Luc Peterson B. K. Spears Brian Van Essen David Hysom Jae-Seung Yeom Tim Moon
+	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
+	Understanding Deep Neural Networks through Input Uncertainties	2019	Jayaraman J. Thiagarajan Irene Kim Rushil Anirudh Peer‐Timo Bremer
+	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
+	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
+	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
+	Parallelizing Training of Deep Generative Models on Massive Scientific Datasets	2019	Sam Adé Jacobs Brian Van Essen David Hysom Jae-Seung Yeom Tim Moon Rushil Anirudh Jayaraman J. Thiagaranjan Shusen Liu Peer‐Timo Bremer Jim Gaffney
+	Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors	2019	Jayaraman J. Thiagarajan Bindya Venkatesh Prasanna Sattigeri Peer‐Timo Bremer
+	MimicGAN: Corruption-Mimicking for Blind Image Recovery & Adversarial Defense	2018	Rushil Anirudh Jayaraman J. Thiagarajan Bhavya Kailkhura Peer‐Timo Bremer
+	Understanding Deep Neural Networks through Input Uncertainties	2018	Jayaraman J. Thiagarajan Irene Kim Rushil Anirudh Peer‐Timo Bremer
+	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
+ 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	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
+	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
+	Understanding Deep Neural Networks through Input Uncertainties	2018	Jayaraman J. Thiagarajan Irene Kim Rushil Anirudh 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 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
+	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
+	Data-Driven Metric Learning for History Matching	2017	Jacob Miller Jayaraman J. Thiagarajan Peer‐Timo Bremer Nazish Hoda Dave Stern Rick T. Mifflin
+	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
+	Local, smooth, and consistent Jacobi set simplification	2014	Harsh Bhatia Bei Wang Gregory Norgard Valerio Pascucci Peer‐Timo Bremer
+	Robust Detection of Singularities in Vector Fields	2014	Harsh Bhatia Attila Gyulassy Hao Wang Peer‐Timo Bremer Valerio Pascucci
+	Robust Detection of Singularities in Vector Fields.	2014	Harsh Bhatia Attila Gyulassy Hao Wang Peer‐Timo Bremer Valerio Pascucci
+	Local, Smooth, and Consistent Jacobi Set Simplification	2013	Harsh Bhatia Bei Wang Gregory Norgard Valerio Pascucci Peer‐Timo Bremer
+	Local, Smooth, and Consistent Jacobi Set Simplification	2013	Harsh Bhatia Bei Wang Gregory Norgard Valerio Pascucci Peer‐Timo Bremer
+ PDF Chat	ADAPTIVE SAMPLING WITH TOPOLOGICAL SCORES	2012	Dan Maljovec Bei Wang Ana Kupresanin Gardar Johannesson Valerio Pascucci Peer‐Timo Bremer
+	Robust computation of Morse–Smale complexes of bilinear functions	2012	Gregory Norgard Peer‐Timo Bremer
+	Heat release and turbulence statistics from a DNS of reacting jet in cross-flow parameterized in a jet natural coordinate system developed from scalar quantities.	2011	Janine Camille Bennett Jacqueline H. Chen Ray Grout Peer‐Timo Bremer Andrea Gruber Attila Gyulassy
+	Robust Computation of Morse-Smale Complexes of Bilinear Functions	2010	Gregory Norgard Peer‐Timo Bremer

Common Coauthors

Coauthor	Papers Together
Jayaraman J. Thiagarajan	61
Rushil Anirudh	50
B. K. Spears	21
Bhavya Kailkhura	20
Jim Gaffney	16
Valerio Pascucci	16
Shusen Liu	14
Harsh Bhatia	14
Brian Van Essen	8
Peter Robinson	7
Jae-Seung Yeom	7
Bogdan Kustowski	7
Sam Adé Jacobs	7
Andreas Spanias	6
David Hysom	6
Attila Gyulassy	5
Gregory Norgard	5
Haichao Miao	5
J. L. Peterson	5
Gemma J. Anderson	5
Luc Peterson	5
Rahul Sridhar	5
T. Ma	4
Bei Wang	4
Vivek Narayanaswamy	4
X. Q. Xu	4
Frederick H. Streitz	4
Sara Y. Del Valle	4
Timothy C. Germann	4
Gowtham Muniraju	4
Kyle Champley	4
Bindya Venkatesh	4
Zhimin Li	3
Kevin Athey	3
Dan Maljovec	3
Robert Cerda	3
Brian Thomas Weston	3
Joseph Koning	3
Jayaraman J. Thiagaranjan	3
Hyojin Kim	3
Kelli Humbird	3
Brian Au	3
Prasanna Sattigeri	3
Matthew Olson	3
Jessica Semler	3
Irene Kim	3
Vuthea Chheang	3
Tim Moon	3
Karthikeyan Natesan Ramamurthy	3
Tom Benson	3

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ 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
+ 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	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
+ PDF Chat	Deep Residual Learning for Image Recognition	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	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
+	Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning	2015	Yarin Gal Zoubin Ghahramani	5
+	Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning	2015	Yarin Gal Zoubin Ghahramani	5
+	Searching for exotic particles in high-energy physics with deep learning	2014	Pierre Baldi Peter Sadowski D. Whiteson	5
+	A Unified Approach to Interpreting Model Predictions	2017	Scott Lundberg Su‐In Lee	5
+	On Calibration of Modern Neural Networks	2017	Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger	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
+ PDF Chat	Deep Learning Face Attributes in the Wild	2015	Ziwei Liu Ping Luo Xiaogang Wang Xiaoou Tang	4
+	Wasserstein Auto-Encoders	2018	Ilya Tolstikhin Olivier Bousquet Sylvain Gelly Bernhard Schölkopf	4
+ PDF Chat	Towards Evaluating the Robustness of Neural Networks	2017	Nicholas Carlini David Wagner	4
+	Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks	2015	Alec Radford Luke Metz Soumith Chintala	4
+	Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data	2019	Yinhao Zhu Nicholas Zabaras Phaedon‐Stelios Koutsourelakis Paris Perdikaris	4
+	Explaining and Harnessing Adversarial Examples	2014	Ian Goodfellow Jonathon Shlens Christian Szegedy	4
+ PDF Chat	Solving Linear Inverse Problems Using Gan Priors: An Algorithm with Provable Guarantees	2018	Viraj Shah Chinmay Hegde	4
+ PDF Chat	Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks	2017	Jun-Yan Zhu Taesung Park Phillip Isola Alexei A. Efros	4
+ PDF Chat	Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification	2018	Rohit Tripathy Ilias Bilionis	4
+	Deep Neural Network Initialization With Decision Trees	2018	Kelli Humbird J. L. Peterson Ryan G. McClarren	4
+	Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps	2013	Karen Simonyan Andrea Vedaldi Andrew Zisserman	4
+	Solving Bilinear Inverse Problems using Deep Generative Priors.	2018	Muhammad Asim Fahad Shamshad Ali Ahmed	4
+ 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	4
+	Monte Carlo and Quasi-Monte Carlo for Statistics	2009	Art B. Owen	4
+ 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	4
+ PDF Chat	Zero-Shot Super-Resolution Using Deep Internal Learning	2018	Assaf Shocher Nadav Cohen Michal Irani	3
+	Adam: A Method for Stochastic Optimization	2014	Diederik P. Kingma Jimmy Ba	3
+	Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles	2016	Balaji Lakshminarayanan Alexander Pritzel Charles Blundell	3
+ PDF Chat	Inverting the Generator of a Generative Adversarial Network	2018	Antonia Creswell Anil A. Bharath	3
+ 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	3
+ PDF Chat	Granger-Causal Attentive Mixtures of Experts: Learning Important Features with Neural Networks	2019	Patrick Schwab Djordje Miladinovic Walter Karlen	3
+ PDF Chat	Image-to-Image Translation with Conditional Adversarial Networks	2017	Phillip Isola Jun-Yan Zhu Tinghui Zhou Alexei A. Efros	3
+ PDF Chat	Learning for Single-Shot Confidence Calibration in Deep Neural Networks Through Stochastic Inferences	2019	Seonguk Seo Paul Hongsuck Seo Bohyung Han	3
+	Measuring Calibration in Deep Learning	2019	Jeremy Nixon Mike Dusenberry Ghassen Jerfel Timothy Nguyen Jeremiah Zhe Liu Linchuan Zhang Dustin Tran	3
+	Accurate Uncertainties for Deep Learning Using Calibrated Regression	2018	Volodymyr Kuleshov Nathan Fenner Stefano Ermon	3
+	Multilevel Techniques for Compression and Reduction of Scientific Data---The Multivariate Case	2019	Mark Ainsworth Ozan Tuğluk Ben Whitney Scott Klasky	3
+ PDF Chat	Bayesian deep convolutional encoder–decoder networks for surrogate modeling and uncertainty quantification	2018	Yinhao Zhu Nicholas Zabaras	3
+	Compressed Sensing using Generative Models	2017	Ashish Bora Ajil Jalal Eric Price Alexandros G. Dimakis	3
+	Optimizing the Latent Space of Generative Networks	2017	Piotr Bojanowski Armand Joulin David López-Paz Arthur Szlam	3
+	Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms	2017	Xiao Han Kashif Rasul Roland Vollgraf	3
+	Learning Important Features Through Propagating Activation Differences	2017	Avanti Shrikumar Peyton Greenside Anshul Kundaje	3
+ PDF Chat	A Suite of Mechanistic Epidemiological Decision Support Tools	2018	Paul W. Fenimore Benjamin H. McMahon Nicolas Hengartner Timothy C. Germann Judith R. Mourant	3
+	TTHRESH: Tensor Compression for Multidimensional Visual Data	2019	Rafael Ballester‐Ripoll Peter Lindström Renato Pajarola	3
+ PDF Chat	One Network to Solve Them All — Solving Linear Inverse Problems Using Deep Projection Models	2017	Je-Yuan Chang Chun‐Liang Li Barnabás Póczos B. V. K. Vijaya Kumar Aswin C. Sankaranarayanan	3
+ PDF Chat	Uncertainties in Parameters Estimated with Neural Networks: Application to Strong Gravitational Lensing	2017	Laurence Perreault-Levasseur Yashar Hezaveh Risa H. Wechsler	3
+	Context Encoders: Feature Learning by Inpainting	2016	Deepak Pathak Philipp Krähenbühl Jeff Donahue Trevor Darrell Alexei A. Efros	3
+ PDF Chat	Hierarchical Morse--Smale Complexes for Piecewise Linear 2-Manifolds	2003	Herbert Edelsbrunner John Harer Afra Zomorodian	3
+ PDF Chat	Generative Visual Manipulation on the Natural Image Manifold	2016	Jun-Yan Zhu Philipp Krähenbühl Eli Shechtman Alexei A. Efros	3
+ PDF Chat	Deep Convolutional Neural Network for Inverse Problems in Imaging	2017	Kyong Hwan Jin Michael T. McCann Emmanuel Froustey Michaël Unser	3