The work of former postdoc Dr. Han with professors Lee and Gelb, "Learning inbetween imagery dynamics via physical latent spaces”, has been published in the SIAM Journal on Scientific Computing. The work proposes a framework to learn the underlying dynamics between two images observed at consecutive time steps. The proposed method focuses on estimating the intermediary stages of image evolution, allowing for interpretability through latent dynamics while preserving spatial correlations with the image. By incorporating a latent variable that follows a physical model expressed in partial differential equations, the approach ensures the interpretability of the learned model and provides insight into corresponding image dynamics. The work also provides a series of numerical tests, including real SAR data, to demonstrate the robustness and effectiveness of the new framework. Click the video below for higher resolution. More demonstrations (including videos) can be found here.
Professor Dan Rockmore is featured in the Faculty of Arts and Sciences article “Shining a Spotlight on Humanity in a Digital Era”.
Tadashi Tokieda of Stanford University will give the 2024 Reese T. Prosser Memorial Lecture, titled A world from a sheet of paper at 6 p.m. on Friday, October 4 in 008 Kemeny. (Click/tap image for full size poster.)
Asher Auel, Avinash Kulkarni, Jack Petok, Jonah Weinbaum
Mathematics of Computation
Asher Auel, V. Suresh
Algebra & Number Theory
Ahmad Reza Haj Saeedi Sadegh, Shiqi Liu, Yiannis Loizides, Jesus Sanchez
Journal of Functional Analysis
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