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The Department of Applied Mathematics weekly seminar is given by scholars and researchers working in applied mathematics, broadly interpreted. Title: Operator learning meets inverse problems
The Department of Applied Mathematics weekly seminar is given by scholars and researchers working in applied mathematics, broadly interpreted. Title: Bayesian Inversion for Linear Autonomous Dynamical Systems with Application to Real-Time Tsunami Forecasting in Cascadia
The Department of Applied Mathematics is pleased to host this series of colloquium lectures, funded in part by a generous gift from the Boeing Company. This series will bring to campus prominent applied mathematicians from around the world.Title: Randomized algorithms for linear algebraic computations
The Department of Applied Mathematics weekly seminar is given by scholars and researchers working in applied mathematics, broadly interpreted. Title: Offline risk score and policy learning for responsible allocation of scarce housing to people experiencing homelessness
The Department of Applied Mathematics weekly seminar is given by scholars and researchers working in applied mathematics, broadly interpreted. Title: Fast cut cell quadratures and robust contouring algorithms
The Department of Applied Mathematics weekly seminar is given by scholars and researchers working in applied mathematics, broadly interpreted. Title: Learning Guarantees for Data-Driven Sparse Sensing and Nonlinear System Identification
Tim Leung was interviewed by The Olympian: Popular Pierce County distillery closed tasting rooms. Is crypto the reason?
By Tom Trogdon, I’m honored to step in as the ninth Chair of Applied Mathematics at the University of Washington. With this honor comes a very challenging time. Because of budgetary pressures at all levels, in cooperation with many departments on campus, we are being forced to rethink the future of higher education.
The Department of Applied Mathematics weekly seminar is given by scholars and researchers working in applied mathematics, broadly interpreted. Title: Iteratively reweighted kernel machines efficiently learn sparse functions