Presenter: Dr. Truong Vu, IPAM and MSU Description: We present a framework for the gradient flow of sharp-interface surface energies that couple to embedded curvature active agents. We use a […]
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Presenter: Dr. Truong Vu, IPAM and MSU Description: We present a framework for the gradient flow of sharp-interface surface energies that couple to embedded curvature active agents. We use a […] |
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Presenter: Katie Schmidt, UQ & Optimization Group Leader, Lawrence Livermore National Laboratory Description: Due to the time and expense associated with physical experiments, there is significant interest in optimal selection […]
Virtual Event
Virtual Event
Presenter: Dr. Danielle Robinson, AWS AI Description: In this talk, I will discuss the large impact of foundation models within the sciences with a particular focus on the importance of […]
Not sure if graduate school is right for you? Join us to learn what graduate school is really about and explore whether it’s the right path for you. We’ll cover topics such as qualifying exams, funding options, common misconceptions, and more! Click the link below to register for the event: https://ucsc.zoom.us/webinar/register/WN_31OHhwc7QPqJ7nSyiuAUNg |
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Hybrid Event
Hybrid Event
Presenter: Subhadeep Paul, Associate Professor, Ohio State University Description: In the first part of the talk, we consider the problem of Transfer Learning (TL) under heterogeneity from a source to […] |
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Virtual Event
Virtual Event
Presenter: Guannan Wang, Associate Professor, The College of William & Mary Description: Generative AI has emerged as a powerful tool for synthesizing biomedical images, offering new solutions to challenges such […]
Virtual Event
Virtual Event
Presenter: Fabrizio Falasca, New York University Description: A central challenge in climate science and applied mathematics is developing data-driven models of multiscale systems that capture both stationary statistics and responses […] |
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Virtual Event
Virtual Event
Presenter: Yunyi Shen, Ph.D. Candidate, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology Description: Practitioners often aim to infer an unobserved population trajectory using sample snapshots at […] |
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