9 citations · 16 across the 4 of their papers we have counts for
4 papers
Automated and Autonomous Experiment in Electron and Scanning Probe Microscopy
Sergei V. Kalinin, Maxim A. Ziatdinov, Jacob Hinkle +6
Machine learning and artificial intelligence (ML/AI) are rapidly becoming an indispensable part of physics research, with domain applications ranging from theory and materials pred…
Computer-aided abnormality detection in chest radiographs in a clinical setting via domain-adaptation
Abhishek K Dubey, Michael T Young, Christopher Stanley +2
Deep learning (DL) models are being deployed at medical centers to aid radiologists for diagnosis of lung conditions from chest radiographs. Such models are often trained on a larg…
Learning nonlinear level sets for dimensionality reduction in function approximation
Guannan Zhang, Jiaxin Zhang, Jacob Hinkle
We developed a Nonlinear Level-set Learning (NLL) method for dimensionality reduction in high-dimensional function approximation with small data. This work is motivated by a variet…
Polynomial Regression on Riemannian Manifolds
Jacob Hinkle, Prasanna Muralidharan, P. Thomas Fletcher +1
In this paper we develop the theory of parametric polynomial regression in Riemannian manifolds and Lie groups. We show application of Riemannian polynomial regression to shape ana…