Jacob D. Hinkle

Orcid: 0000-0002-7751-1760

According to our database1, Jacob D. Hinkle authored at least 33 papers between 2009 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
Scaling Resolution of Gigapixel Whole Slide Images Using Spatial Decomposition on Convolutional Neural Networks.
Proceedings of the Platform for Advanced Scientific Computing Conference, 2023

2022
Model Assumptions and Data Characteristics: Impacts on Domain Adaptation in Building Segmentation.
IEEE Trans. Geosci. Remote. Sens., 2022

Image Gradient Decomposition for Parallel and Memory-Efficient Ptychographic Reconstruction.
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.
Proceedings of the IEEE International Conference on Big Data, 2022

2021
Convolutional neural network based non-iterative reconstruction for accelerating neutron tomography.
Mach. Learn. Sci. Technol., 2021

Automated and Autonomous Experiment in Electron and Scanning Probe Microscopy.
CoRR, 2021

Distributed Training for High Resolution Images: A Domain and Spatial Decomposition Approach.
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.
Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies, 2021

2020
Distributed Bayesian optimization of deep reinforcement learning algorithms.
J. Parallel Distributed Comput., 2020

Wide Neural Networks with Bottlenecks are Deep Gaussian Processes.
J. Mach. Learn. Res., 2020

Model Reduction of Shallow CNN Model for Reliable Deployment of Information Extraction from Medical Reports.
CoRR, 2020

Automated detection of pitting and stress corrosion cracks in used nuclear fuel dry storage canisters using residual neural networks.
CoRR, 2020

Toward Large-Scale Image Segmentation on Summit.
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.
CoRR, 2019

Classifying cancer pathology reports with hierarchical self-attention networks.
Artif. Intell. Medicine, 2019

Learning nonlinear level sets for dimensionality reduction in function approximation.
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.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019

Selective Information Extraction Strategies for Cancer Pathology Reports with Convolutional Neural Networks.
Proceedings of the Recent Advances in Big Data and Deep Learning, 2019

Deep Transfer Learning Across Cancer Registries for Information Extraction from Pathology Reports.
Proceedings of the 2019 IEEE EMBS International Conference on Biomedical & Health Informatics, 2019

Extraction of Tumor Site from Cancer Pathology Reports using Deep Filters.
Proceedings of the 10th ACM International Conference on Bioinformatics, 2019

2018
HyperSpace: Distributed Bayesian Hyperparameter Optimization.
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.
Proceedings of the 2017 IEEE International Conference on Image Processing, 2017

2016
Hierarchical Geodesic Models in Diffeomorphisms.
Int. J. Comput. Vis., 2016

2014
Intrinsic Polynomials for Regression on Riemannian Manifolds.
J. Math. Imaging Vis., 2014

An efficient parallel algorithm for hierarchical geodesic models in diffeomorphisms.
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.
Proceedings of the 10th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2013

A Hierarchical Geodesic Model for Diffeomorphic Longitudinal Shape Analysis.
Proceedings of the Information Processing in Medical Imaging, 2013

IDiff: Irrotational Diffeomorphisms for Computational Anatomy.
Proceedings of the Information Processing in Medical Imaging, 2013

2012
4D CT image reconstruction with diffeomorphic motion model.
Medical Image Anal., 2012

Polynomial Regression on Riemannian Manifolds.
Proceedings of the Computer Vision - ECCV 2012, 2012

2011
Quantifying variability in radiation dose due to respiratory-induced tumor motion.
Medical Image Anal., 2011

2010
4D MAP MRI Image Reconstruction.
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.
Proceedings of the Information Processing in Medical Imaging, 2009


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