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Jacob D. Hinkle
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2020 – today
- 2024
- [i10]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:
VISION: Toward a Standardized Process for Radiology Image Management at the National Level. CoRR abs/2404.18842 (2024) - [i9]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:
Domain Shift Analysis in Chest Radiographs Classification in a Veterans Healthcare Administration Population. CoRR abs/2407.21149 (2024) - 2023
- [c20]Aristeidis Tsaris
, Joshua Romero
Scaling Resolution of Gigapixel Whole Slide Images Using Spatial Decomposition on Convolutional Neural Networks. PASC 2023: 2:1-2:11 - 2022
- [j9]Philipe A. Dias
Model Assumptions and Data Characteristics: Impacts on Domain Adaptation in Building Segmentation. IEEE Trans. Geosci. Remote. Sens. 60: 1-18 (2022) - [c19]Folami Alamudun, Jacob D. Hinkle, Sajal Dash
Distilling Knowledge from Ensembles of Cluster-Constrained-Attention Multiple-Instance Learners for Whole Slide Image Classification. IEEE Big Data 2022: 3393-3397 - [c18]Xiao Wang
Image Gradient Decomposition for Parallel and Memory-Efficient Ptychographic Reconstruction. SC 2022: 8:1-8:13 - [i8]Xiao Wang, Aristeidis Tsaris, Debangshu Mukherjee, Mohamed Wahib, Peng Chen, Mark Oxley, Olga Ovchinnikova, Jacob D. Hinkle:
Image Gradient Decomposition for Parallel and Memory-Efficient Ptychographic Reconstruction. CoRR abs/2205.06327 (2022) - 2021
- [j8]Singanallur V. Venkatakrishnan
Convolutional neural network based non-iterative reconstruction for accelerating neutron tomography. Mach. Learn. Sci. Technol. 2(2): 25031 (2021) - [c17]Abhishek Kumar Dubey, Michael T. Young, Christopher B. Stanley
Computer-aided Abnormality Detection in Chest Radiographs in a Clinical Setting via Domain-adaptation. BIOIMAGING 2021: 65-72 - [c16]Aristeidis Tsaris, Jacob D. Hinkle, Dalton D. Lunga, Philipe Ambrozio Dias:
Distributed Training for High Resolution Images: A Domain and Spatial Decomposition Approach. RSDHA@SC 2021: 27-33 - [i7]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:
Automated and Autonomous Experiment in Electron and Scanning Probe Microscopy. CoRR abs/2103.12165 (2021) - 2020
- [j7]Devanshu Agrawal, Theodore Papamarkou
Wide Neural Networks with Bottlenecks are Deep Gaussian Processes. J. Mach. Learn. Res. 21: 175:1-175:66 (2020) - [j6]M. Todd Young, Jacob D. Hinkle
Distributed Bayesian optimization of deep reinforcement learning algorithms. J. Parallel Distributed Comput. 139: 43-52 (2020) - [c15]Sudip K. Seal, Seung-Hwan Lim, Dali Wang, Jacob D. Hinkle, Dalton D. Lunga, Aristeidis Tsaris:
Toward Large-Scale Image Segmentation on Summit. ICPP 2020: 27:1-27:11 - [i6]Devanshu Agrawal, Theodore Papamarkou, Jacob D. Hinkle:
Wide Neural Networks with Bottlenecks are Deep Gaussian Processes. CoRR abs/2001.00921 (2020) - [i5]Theodore Papamarkou, Hayley Guy, Bryce Kroencke, Jordan Miller, Preston Robinette, Daniel Schultz, Jacob D. Hinkle, Laura Pullum, Catherine D. Schuman, Jeremy Renshaw, Stylianos Chatzidakis:
Automated detection of pitting and stress corrosion cracks in used nuclear fuel dry storage canisters using residual neural networks. CoRR abs/2003.03241 (2020) - [i4]Abhishek Kumar Dubey, Alina Peluso, Jacob D. Hinkle, Devanshu Agarawal, Zilong Tan:
Model Reduction of Shallow CNN Model for Reliable Deployment of Information Extraction from Medical Reports. CoRR abs/2008.01572 (2020) - [i3]Abhishek Kumar Dubey, Michael T. Young, Christopher B. Stanley, Dalton D. Lunga, Jacob D. Hinkle:
Computer-aided abnormality detection in chest radiographs in a clinical setting via domain-adaptation. CoRR abs/2012.10564 (2020)
2010 – 2019
- 2019
- [j5]Shang Gao, John X. Qiu, Mohammed M. Alawad, Jacob D. Hinkle
Classifying cancer pathology reports with hierarchical self-attention networks. Artif. Intell. Medicine 101 (2019) - [c14]Abhishek Kumar Dubey, Jacob D. Hinkle
Extraction of Tumor Site from Cancer Pathology Reports using Deep Filters. BCB 2019: 320-327 - [c13]Mohammed M. Alawad, Shang Gao, John X. Qiu, Noah Schaefferkoetter, Jacob D. Hinkle
Deep Transfer Learning Across Cancer Registries for Information Extraction from Pathology Reports. BHI 2019: 1-4 - [c12]Hong-Jun Yoon, John X. Qiu, James Blair Christian, Jacob D. Hinkle, Folami Alamudun
Selective Information Extraction Strategies for Cancer Pathology Reports with Convolutional Neural Networks. INNSBDDL 2019: 89-98 - [c11]Devanshu Agrawal, Hong-Jun Yoon, Georgia D. Tourassi, Jacob D. Hinkle
Computer-aided detection using non-convolutional neural network Gaussian processes. Medical Imaging: Computer-Aided Diagnosis 2019: 109503N - [c10]Guannan Zhang, Jiaxin Zhang, Jacob D. Hinkle:
Learning nonlinear level sets for dimensionality reduction in function approximation. NeurIPS 2019: 13199-13208 - [i2]Theodore Papamarkou, Jacob D. Hinkle, M. Todd Young, David E. Womble:
Challenges in Bayesian inference via Markov chain Monte Carlo for neural networks. CoRR abs/1910.06539 (2019) - 2018
- [c9]M. Todd Young, Jacob D. Hinkle
HyperSpace: Distributed Bayesian Hyperparameter Optimization. SBAC-PAD 2018: 339-347 - 2017
- [c8]Prasanna Muralidharan, Jacob D. Hinkle
A map estimation algorithm for Bayesian polynomial regression on riemannian manifolds. ICIP 2017: 215-219 - 2016
- [j4]Nikhil Singh, Jacob D. Hinkle
Hierarchical Geodesic Models in Diffeomorphisms. Int. J. Comput. Vis. 117(1): 70-92 (2016) - 2014
- [j3]Jacob D. Hinkle
Intrinsic Polynomials for Regression on Riemannian Manifolds. J. Math. Imaging Vis. 50(1-2): 32-52 (2014) - [c7]Nikhil Singh, Jacob D. Hinkle, Sarang C. Joshi, P. Thomas Fletcher:
An efficient parallel algorithm for hierarchical geodesic models in diffeomorphisms. ISBI 2014: 341-344 - 2013
- [c6]Nikhil Singh, Jacob D. Hinkle
A Hierarchical Geodesic Model for Diffeomorphic Longitudinal Shape Analysis. IPMI 2013: 560-571 - [c5]Jacob D. Hinkle
IDiff: Irrotational Diffeomorphisms for Computational Anatomy. IPMI 2013: 754-765 - [c4]Nikhil Singh, Jacob D. Hinkle
A vector momenta formulation of diffeomorphisms for improved geodesic regression and atlas construction. ISBI 2013: 1219-1222 - 2012
- [j2]Jacob D. Hinkle
4D CT image reconstruction with diffeomorphic motion model. Medical Image Anal. 16(6): 1307-1316 (2012) - [c3]Jacob D. Hinkle
Polynomial Regression on Riemannian Manifolds. ECCV (3) 2012: 1-14 - [i1]Jacob D. Hinkle, Prasanna Muralidharan, P. Thomas Fletcher, Sarang C. Joshi:
Polynomial Regression on Riemannian Manifolds. CoRR abs/1201.2395 (2012) - 2011
- [j1]Sarah E. Geneser, Jacob D. Hinkle
Quantifying variability in radiation dose due to respiratory-induced tumor motion. Medical Image Anal. 15(4): 640-649 (2011) - 2010
- [c2]Jacob D. Hinkle, Ganesh Adluru, Eugene G. Kholmovski, Edward V. R. Di Bella, Sarang C. Joshi:
4D MAP MRI Image Reconstruction. VISAPP (1) 2010: 251-257
2000 – 2009
- 2009
- [c1]Jacob D. Hinkle
4D MAP Image Reconstruction Incorporating Organ Motion. IPMI 2009: 676-687
Coauthor Index
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