4D MAP Image Reconstruction Incorporating Organ Motion. - Jacob D. Hinkle; P. Thomas Fletcher; Brian Wang; Bill Salter; Sarang C. Joshi (IPMI, 2009)

4D MAP MRI Image Reconstruction. - Jacob D. Hinkle; Ganesh Adluru; Eugene G. Kholmovski; Edward V. R. Di Bella; Sarang C. Joshi (VISAPP (1), 2010)

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)

Polynomial Regression on Riemannian Manifolds. - Jacob D. Hinkle; Prasanna Muralidharan; P. Thomas Fletcher; Sarang C. Joshi (ECCV (3), 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)

IDiff: Irrotational Diffeomorphisms for Computational Anatomy. - Jacob D. Hinkle; Sarang C. Joshi (IPMI, 2013)

A Hierarchical Geodesic Model for Diffeomorphic Longitudinal Shape Analysis. - Nikhil Singh 002; Jacob D. Hinkle; Sarang C. Joshi; P. Thomas Fletcher (IPMI, 2013)

A vector momenta formulation of diffeomorphisms for improved geodesic regression and atlas construction. - Nikhil Singh 002; Jacob D. Hinkle; Sarang C. Joshi; P. Thomas Fletcher (ISBI, 2013)

An efficient parallel algorithm for hierarchical geodesic models in diffeomorphisms. - Nikhil Singh 002; Jacob D. Hinkle; Sarang C. Joshi; P. Thomas Fletcher (ISBI, 2014)

Intrinsic Polynomials for Regression on Riemannian Manifolds. - Jacob D. Hinkle; P. Thomas Fletcher; Sarang C. Joshi (J. Math. Imaging Vis., 2014)

Hierarchical Geodesic Models in Diffeomorphisms. - Nikhil Singh 002; Jacob D. Hinkle; Sarang C. Joshi; P. Thomas Fletcher (Int. J. Comput. Vis., 2016)

A map estimation algorithm for Bayesian polynomial regression on riemannian manifolds. - Prasanna Muralidharan; Jacob D. Hinkle; P. Thomas Fletcher (ICIP, 2017)

HyperSpace: Distributed Bayesian Hyperparameter Optimization. - M. Todd Young; Jacob D. Hinkle; Arvind Ramanathan; Ramakrishnan Kannan (SBAC-PAD, 2018)

Extraction of Tumor Site from Cancer Pathology Reports using Deep Filters. - Abhishek Kumar Dubey; Jacob D. Hinkle; James Blair Christian; Georgia D. Tourassi (BCB, 2019)

Deep Transfer Learning Across Cancer Registries for Information Extraction from Pathology Reports. - Mohammed M. Alawad; Shang Gao 008; 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; et al. (BHI, 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 (INNSBDDL, 2019)

Computer-aided detection using non-convolutional neural network Gaussian processes. - Devanshu Agrawal; Hong-Jun Yoon; Georgia D. Tourassi; Jacob D. Hinkle (Computer-Aided Diagnosis, 2019)

Learning nonlinear level sets for dimensionality reduction in function approximation. - Guannan Zhang; Jiaxin Zhang 005; Jacob D. Hinkle (NeurIPS, 2019)

Classifying cancer pathology reports with hierarchical self-attention networks. - Shang Gao 008; 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; et al. (Artif. Intell. Medicine, 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)

Toward Large-Scale Image Segmentation on Summit. - Sudip K. Seal; Seung-Hwan Lim; Dali Wang; Jacob D. Hinkle; Dalton D. Lunga; Aristeidis Tsaris (ICPP, 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)

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)

Wide Neural Networks with Bottlenecks are Deep Gaussian Processes. - Devanshu Agrawal; Theodore Papamarkou; Jacob D. Hinkle (J. Mach. Learn. Res., 2020)

Distributed Bayesian optimization of deep reinforcement learning algorithms. - M. Todd Young; Jacob D. Hinkle; Ramakrishnan Kannan; Arvind Ramanathan (J. Parallel Distributed Comput., 2020)

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 (BIOIMAGING, 2021)

Distributed Training for High Resolution Images: A Domain and Spatial Decomposition Approach. - Aristeidis Tsaris; Jacob D. Hinkle; Dalton D. Lunga; Philipe Ambrozio Dias (RSDHA@SC, 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)

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)

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 (IEEE Big Data, 2022)

Image Gradient Decomposition for Parallel and Memory-Efficient Ptychographic Reconstruction. - Xiao Wang 004; Aristeidis Tsaris; Debangshu Mukherjee; Mohamed Wahib; Peng Chen 035; Mark Oxley; Olga Ovchinnikova; Jacob D. Hinkle (SC, 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)

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 (PASC, 2023)

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; et al. (CoRR, 2024)

Domain Shift Analysis in Chest Radiographs Classification in a Veterans Healthcare Administration Population. - Mayanka Chandrashekar; 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; et al. (CoRR, 2024)