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Extracting low-order representations of vortex dominated flows using deep neural networks

Speaker: Barbara Lopez-Doriga, Ph.D. IDRE Postdoctoral Fellow Mechanical and Aerospace Engineering University of California Los Angeles Place: Virtual (Register here for the zoom link)   Abstract: There is significant practical interest in understanding and modeling fluid systems, not only to gain insights into the complex dynamics that govern them, but also to enable their control...

Bridging AI and Generative Models with Mean Field Control through Score Based Normalizing Flow

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Speaker: Mo Zhou, Ph.D. IDRE Postdoctoral Fellow Department of Mathematics (UCLA) University of California Los Angeles    Place: Virtual (Link to the video recording) Abstract:     Generative models, a cornerstone of modern AI, learn to approximate complex probability distributions and generate realistic data. A key challenge in these models is efficiently computing the “score function,”...

TimeAutoDiff : Combining auto-encoder and diffusion model for time series tabular synthesizing

    Speaker: Najoon Suh, Ph.D IDRE Fellow Department of Statistics and Data Science University of California Los Angeles   Location: Zoom (Recording link)   Abstract: In the work to be presented, we leverage the power of latent diffusion models to generate synthetic time series tabular data. Along with the temporal and feature correlations, the...

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