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Dmitry Karpeyev

Showing results (1-10 of 6) with videos related to

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Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|March 14, 2015
Detecting vortices in superconductors: extracting one-dimensional topological singularities from a discretized complex scalar fieldCarolyn L Phillips, Tom Peterka, Dmitry Karpeyev, et al.
ACS Nano|September 11, 2015
Miscibility Gap Closure, Interface Morphology, and Phase Microstructure of 3D Li(x)FePO4 Nanoparticles from Surface Wetting and Coherency StrainMichael J Welland, Dmitry Karpeyev, Devin T O'Connor, et al.
Physical Review. E|March 18, 2016
Tracking vortices in superconductors: Extracting singularities from a discretized complex scalar field evolving in timeCarolyn L Phillips, Hanqi Guo, Tom Peterka, et al.
IEEE Transactions on Visualization and Computer Graphics|November 4, 2015
Extracting, Tracking, and Visualizing Magnetic Flux Vortices in 3D Complex-Valued Superconductor Simulation DataHanqi Guo, Carolyn L Phillips, Tom Peterka, et al.
Nature Communications|November 3, 2022
Uncertainty-informed deep learning models enable high-confidence predictions for digital histopathologyJames M Dolezal, Andrew Srisuwananukorn, Dmitry Karpeyev, et al.
NPJ Precision Oncology|May 29, 2023
Deep learning generates synthetic cancer histology for explainability and educationJames M Dolezal, Rachelle Wolk, Hanna M Hieromnimon, et al.
Pageof 1

Showing results (1-10 of 6) with videos related to

Sort By:
Pageof 1
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|March 14, 2015
Detecting vortices in superconductors: extracting one-dimensional topological singularities from a discretized complex scalar fieldCarolyn L Phillips, Tom Peterka, Dmitry Karpeyev, et al.
ACS Nano|September 11, 2015
Miscibility Gap Closure, Interface Morphology, and Phase Microstructure of 3D Li(x)FePO4 Nanoparticles from Surface Wetting and Coherency StrainMichael J Welland, Dmitry Karpeyev, Devin T O'Connor, et al.
Physical Review. E|March 18, 2016
Tracking vortices in superconductors: Extracting singularities from a discretized complex scalar field evolving in timeCarolyn L Phillips, Hanqi Guo, Tom Peterka, et al.
IEEE Transactions on Visualization and Computer Graphics|November 4, 2015
Extracting, Tracking, and Visualizing Magnetic Flux Vortices in 3D Complex-Valued Superconductor Simulation DataHanqi Guo, Carolyn L Phillips, Tom Peterka, et al.
Nature Communications|November 3, 2022
Uncertainty-informed deep learning models enable high-confidence predictions for digital histopathologyJames M Dolezal, Andrew Srisuwananukorn, Dmitry Karpeyev, et al.
NPJ Precision Oncology|May 29, 2023
Deep learning generates synthetic cancer histology for explainability and educationJames M Dolezal, Rachelle Wolk, Hanna M Hieromnimon, et al.
Pageof 1