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Theodore Papamarkou

Adjunct Professor


My research spans Bayesian deep learning, approximate Monte Carlo methods, and mathematics of deep learning. By conducting research in these areas, I am interested in addressing respective questions in uncertainty quantification for deep learning, approximate inference with big data or with high-dimensional models, and function approximation.

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