Learning
S&DS Colloquium: Thuy-Duong “June” Vuong (Miller Institute, Berkeley), “Efficiently learning and sampling from multimodal distributions using data-based initialization”
Abstract: Learning to sample is a central task in generative AI: the goal is to generate (infinitely many more) samples from a target distribution $\mu$ […]
FDS Colloquium: Houman Owhadi (Caltech), “Co-discovering graphical structure and functional relationships within data: A Gaussian Process framework for connecting the dots”
Abstract: Most scientific challenges can be framed into one of the following three levels of complexity of function approximation. Examples of Type 2 problems include […]
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