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In inverse problems, one would like to reconstruct a spatially variable function from measurements of a system in which this function appears as a coefficient or right-hand side. Examples include biomedical imaging and seismic imaging of the earth. In many inverse problems, practitioners have an intuitive notion of how much one “knows” about the coefficient in different […]

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Details to come. Refreshments will be served before the talk, starting at 2:45.

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The annual IAM retreat will be held on Monday, April 13, 2026, from 9am to 4:30pm, at the Green College Coach House, located at 6201 Cecil Green Park Road. The IAM retreat is a day-long event where graduate students and post-doctoral fellows have the opportunity to share their research with the community in the format […]

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Nonlinear approximation and random sampling are two vital mathematical pillars of machine learning. On the one hand, nonlinear approximation provides flexible models, such as sparse polynomials or deep neural networks, able to accurately represent very complex functions. On the other hand, random sampling allows us to solve data-starved inverse problems via, e.g., compressive sensing. In […]