News

Implcit neural representations for model reduction

New papers present an alternative view of kinematic approximation

New adventure

Moving to Facebook Research

Data-driven time-parallelism accepted into SISC

Data-driven coarse propagation to accelerate convergence

Paper on machine learning error models published in CMAME

Using regression to model approximate-solution errors

Joining SISC editorial board

Becoming Associate Editor

Preprint on model reduction on nonlinear manifolds using deep convolutional autoencoders now available

Using deep learning to overcome Komolgorov-width limitation