Jacob D. Hinkle

According to our database, Jacob D. Hinkle authored at least 35 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Domain Shift Analysis in Chest Radiographs Classification in a Veterans Healthcare Administration Population.

Mayanka Chandra Shekar, Ian Goethert, Md Inzamam Ul Haque, Benjamin McMahon, Sayera Dhaubhadel, Kathryn Knight, Joseph Erdos, Donna Reagan, Caroline Taylor, Peter Kuzmak, John Michael Gaziano, Eileen McAllister, Lauren Costa, Yuk-Lam Ho, Kelly Cho, Suzanne Tamang, Samah Fodeh-Jarad, Olga S. Ovchinnikova, Amy C. Justice, Jacob D. Hinkle, Ioana Danciu

CoRR, 2024

VISION: Toward a Standardized Process for Radiology Image Management at the National Level.

Kathryn Knight, Ioana Danciu, Olga Ovchinnikova, Jacob D. Hinkle, Mayanka Chandra Shekar, Debangshu Mukherjee, Eileen McAllister, Caitlin Rizy, Kelly Cho, Amy C. Justice, Joseph Erdos, Peter Kuzmak, Lauren Costa, Yuk-Lam Ho, Reddy Madipadga, Suzanne Tamang, Ian Goethert

CoRR, 2024

2023

Scaling Resolution of Gigapixel Whole Slide Images Using Spatial Decomposition on Convolutional Neural Networks.

Aristeidis Tsaris, Joshua Romero, Thorsten Kurth, Jacob D. Hinkle, Hong-Jun Yoon, Feiyi Wang, Sajal Dash, Georgia D. Tourassi

Proceedings of the Platform for Advanced Scientific Computing Conference, 2023

2022

Model Assumptions and Data Characteristics: Impacts on Domain Adaptation in Building Segmentation.

Philipe A. Dias, Yuxin Tian, Shawn D. Newsam, Aristeidis Tsaris, Jacob D. Hinkle, Dalton D. Lunga

IEEE Trans. Geosci. Remote. Sens., 2022

Image Gradient Decomposition for Parallel and Memory-Efficient Ptychographic Reconstruction.

Xiao Wang, Aristeidis Tsaris, Debangshu Mukherjee, Mohamed Wahib, Peng Chen, Mark Oxley, Olga Ovchinnikova, Jacob D. Hinkle

Proceedings of the SC22: International Conference for High Performance Computing, 2022

Distilling Knowledge from Ensembles of Cluster-Constrained-Attention Multiple-Instance Learners for Whole Slide Image Classification.

Folami Alamudun, Jacob D. Hinkle, Sajal Dash, Benjamín Hernández, Aristeidis Tsaris, Hong-Jun Yoon

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Convolutional neural network based non-iterative reconstruction for accelerating neutron tomography.

Singanallur V. Venkatakrishnan, Amirkoushyar Ziabari, Jacob D. Hinkle, Andrew W. Needham, Jeffrey M. Warren, Hassina Z. Bilheux

Mach. Learn. Sci. Technol., 2021

Automated and Autonomous Experiment in Electron and Scanning Probe Microscopy.

Sergei V. Kalinin, Maxim A. Ziatdinov, Jacob D. Hinkle, Stephen Jesse, Ayana Ghosh, Kyle P. Kelley, Andrew R. Lupini, Bobby G. Sumpter, Rama K. Vasudevan

CoRR, 2021

Distributed Training for High Resolution Images: A Domain and Spatial Decomposition Approach.

Aristeidis Tsaris, Jacob D. Hinkle, Dalton D. Lunga, Philipe Ambrozio Dias

Proceedings of the IEEE/ACM Redefining Scalability for Diversely Heterogeneous Architectures Workshop, 2021

Computer-aided Abnormality Detection in Chest Radiographs in a Clinical Setting via Domain-adaptation.

Abhishek Kumar Dubey, Michael T. Young, Christopher B. Stanley, Dalton D. Lunga, Jacob D. Hinkle

Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies, 2021

2020

Distributed Bayesian optimization of deep reinforcement learning algorithms.

M. Todd Young, Jacob D. Hinkle, Ramakrishnan Kannan, Arvind Ramanathan

J. Parallel Distributed Comput., 2020

Wide Neural Networks with Bottlenecks are Deep Gaussian Processes.

Devanshu Agrawal, Theodore Papamarkou, Jacob D. Hinkle

J. Mach. Learn. Res., 2020

Model Reduction of Shallow CNN Model for Reliable Deployment of Information Extraction from Medical Reports.

Abhishek Kumar Dubey, Alina Peluso, Jacob D. Hinkle, Devanshu Agarawal, Zilong Tan

CoRR, 2020

Automated detection of pitting and stress corrosion cracks in used nuclear fuel dry storage canisters using residual neural networks.

Theodore Papamarkou, Hayley Guy, Bryce Kroencke, Jordan Miller, Preston Robinette, Daniel Schultz, Jacob D. Hinkle, Laura Pullum, Catherine D. Schuman, Jeremy Renshaw, Stylianos Chatzidakis

CoRR, 2020

Toward Large-Scale Image Segmentation on Summit.

Sudip K. Seal, Seung-Hwan Lim, Dali Wang, Jacob D. Hinkle, Dalton D. Lunga, Aristeidis Tsaris

Proceedings of the ICPP 2020: 49th International Conference on Parallel Processing, 2020

2019

Challenges in Bayesian inference via Markov chain Monte Carlo for neural networks.

Theodore Papamarkou, Jacob D. Hinkle, M. Todd Young, David E. Womble

CoRR, 2019

Classifying cancer pathology reports with hierarchical self-attention networks.

Shang Gao, John X. Qiu, Mohammed M. Alawad, Jacob D. Hinkle, Noah Schaefferkoetter, Hong-Jun Yoon, James Blair Christian, Paul A. Fearn, Lynne Penberthy, Xiao-Cheng Wu, Linda Coyle, Georgia D. Tourassi, Arvind Ramanathan

Artif. Intell. Medicine, 2019

Learning nonlinear level sets for dimensionality reduction in function approximation.

Guannan Zhang, Jiaxin Zhang, Jacob D. Hinkle

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Computer-aided detection using non-convolutional neural network Gaussian processes.

Devanshu Agrawal, Hong-Jun Yoon, Georgia D. Tourassi, Jacob D. Hinkle

Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019

Selective Information Extraction Strategies for Cancer Pathology Reports with Convolutional Neural Networks.

Hong-Jun Yoon, John X. Qiu, James Blair Christian, Jacob D. Hinkle, Folami Alamudun, Georgia D. Tourassi

Proceedings of the Recent Advances in Big Data and Deep Learning, 2019

Deep Transfer Learning Across Cancer Registries for Information Extraction from Pathology Reports.

Mohammed M. Alawad, Shang Gao, John X. Qiu, Noah Schaefferkoetter, Jacob D. Hinkle, Hong-Jun Yoon, James Blair Christian, Xiao-Cheng Wu, Eric B. Durbin, Jong Cheol Jeong, Isaac Hands, David Rust, Georgia D. Tourassi

Proceedings of the 2019 IEEE EMBS International Conference on Biomedical & Health Informatics, 2019

Extraction of Tumor Site from Cancer Pathology Reports using Deep Filters.

Abhishek Kumar Dubey, Jacob D. Hinkle, James Blair Christian, Georgia D. Tourassi

Proceedings of the 10th ACM International Conference on Bioinformatics, 2019

2018

HyperSpace: Distributed Bayesian Hyperparameter Optimization.

M. Todd Young, Jacob D. Hinkle, Arvind Ramanathan, Ramakrishnan Kannan

Proceedings of the 30th International Symposium on Computer Architecture and High Performance Computing, 2018

2017

A map estimation algorithm for Bayesian polynomial regression on riemannian manifolds.

Prasanna Muralidharan, Jacob D. Hinkle, P. Thomas Fletcher

Proceedings of the 2017 IEEE International Conference on Image Processing, 2017

2016

Hierarchical Geodesic Models in Diffeomorphisms.

Nikhil Singh, Jacob D. Hinkle, Sarang C. Joshi, P. Thomas Fletcher

Int. J. Comput. Vis., 2016

2014

Intrinsic Polynomials for Regression on Riemannian Manifolds.

Jacob D. Hinkle, P. Thomas Fletcher, Sarang C. Joshi

J. Math. Imaging Vis., 2014

An efficient parallel algorithm for hierarchical geodesic models in diffeomorphisms.

Nikhil Singh, Jacob D. Hinkle, Sarang C. Joshi, P. Thomas Fletcher

Proceedings of the IEEE 11th International Symposium on Biomedical Imaging, 2014

2013

A vector momenta formulation of diffeomorphisms for improved geodesic regression and atlas construction.

Nikhil Singh, Jacob D. Hinkle, Sarang C. Joshi, P. Thomas Fletcher

Proceedings of the 10th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2013

A Hierarchical Geodesic Model for Diffeomorphic Longitudinal Shape Analysis.

Nikhil Singh, Jacob D. Hinkle, Sarang C. Joshi, P. Thomas Fletcher

Proceedings of the Information Processing in Medical Imaging, 2013

IDiff: Irrotational Diffeomorphisms for Computational Anatomy.

Jacob D. Hinkle, Sarang C. Joshi

Proceedings of the Information Processing in Medical Imaging, 2013

2012

4D CT image reconstruction with diffeomorphic motion model.

Jacob D. Hinkle, Martin Szegedi, Brian Wang, Bill Salter, Sarang C. Joshi

Medical Image Anal., 2012

Polynomial Regression on Riemannian Manifolds.

Jacob D. Hinkle, Prasanna Muralidharan, P. Thomas Fletcher, Sarang C. Joshi

Proceedings of the Computer Vision - ECCV 2012, 2012

2011

Quantifying variability in radiation dose due to respiratory-induced tumor motion.

Sarah E. Geneser, Jacob D. Hinkle, Robert M. Kirby, Brian Wang, Bill Salter, Sarang C. Joshi

Medical Image Anal., 2011

2010

4D MAP MRI Image Reconstruction.

Jacob D. Hinkle, Ganesh Adluru, Eugene G. Kholmovski, Edward V. R. Di Bella, Sarang C. Joshi

Proceedings of the VISAPP 2010 - Proceedings of the Fifth International Conference on Computer Vision Theory and Applications, Angers, France, May 17-21, 2010, 2010

2009

4D MAP Image Reconstruction Incorporating Organ Motion.

Jacob D. Hinkle, P. Thomas Fletcher, Brian Wang, Bill Salter, Sarang C. Joshi

Proceedings of the Information Processing in Medical Imaging, 2009