Our seminar focuses on efficient computational methods for numerical problems, mostly phrased in a mathematical language, arising in areas of science throughout the Institute and beyond. Topics include signal processing and data analysis (neural spike sorting, cryo-EM, imaging); computational statistics (Bayesian, MCMC, variational, robust inference, microbiome); deep learning (equivariant networks); PDEs (fluid flow, wave scattering), integral equations, spectral methods, fast algorithms (i.e., close to optimal complexity); software libraries and programming. We discuss research topics as well as review classical topics in numerical analysis and statistics.
Time: 10am-11:30am on Wednesdays, unless as announced.
Location: 162 Fifth Avenue, 3rd-floor classroom / Virtual.
All from Flatiron are welcome, and guests from outside must arrange a visitor’s pass.