Search Results for author: Michael E. Glinsky

Found 7 papers, 0 papers with code

The inherent goodness of well educated intelligence

no code implementations9 Jan 2024 Michael E. Glinsky

Special attention will be paid to the being having the ability to characterize and control a collective system of many identical conservative sub-systems conservatively interacting.

A new economic and financial theory of money

no code implementations8 Oct 2023 Michael E. Glinsky, Sharon Sievert

The view of electronic currency as a transactional equity associated with tangible assets of a sub-economy will be developed, in contrast to the view of stock as an equity associated mostly with intangible assets of a sub-economy.

Decision Making

Noise-resilient approach for deep tomographic imaging

no code implementations22 Nov 2022 Zhen Guo, Zhiguang Liu, Qihang Zhang, George Barbastathis, Michael E. Glinsky

We propose a noise-resilient deep reconstruction algorithm for X-ray tomography.

Physics-assisted Generative Adversarial Network for X-Ray Tomography

no code implementations7 Apr 2022 Zhen Guo, Jung Ki Song, George Barbastathis, Michael E. Glinsky, Courtenay T. Vaughan, Kurt W. Larson, Bradley K. Alpert, Zachary H. Levine

X-ray tomography is capable of imaging the interior of objects in three dimensions non-invasively, with applications in biomedical imaging, materials science, electronic inspection, and other fields.

Generative Adversarial Network

Quantification of MagLIF morphology using the Mallat Scattering Transformation

no code implementations13 Apr 2020 Michael E. Glinsky, Thomas W. Moore, William E. Lewis, Matthew R. Weis, Christopher A. Jennings, David J. Ampleford, Patrick F. Knapp, Eric C. Harding, Matthew. R. Gomez, Adam J. Harvey-Thompson

We have developed a metric of image morphology based on the Mallat Scattering Transformation (MST), a transformation that has proved to be effective at distinguishing textures, sounds, and written characters.

Quantification of MagLIF morphology using the Mallat Scattering Transformation

no code implementations1 Nov 2019 Michael E. Glinsky, Thomas W. Moore, William E. Lewis, Matthew R. Weis, Christopher A. Jennings, David A. Ampleford, Eric C. Harding, Patrick F. Knapp, Matthew. R. Gomez, Sophia E. Lussiez

We have developed a metric of image morphology based on the Mallat Scattering Transformation (MST), a transformation that has proved to be effective at distinguishing textures, sounds, and written characters.

Computational Physics High Energy Physics - Theory Fluid Dynamics Plasma Physics

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