We consider the problem of approximating a function in general nonlinear...
Numerical methods for random parametric PDEs can greatly benefit from
ad...
We consider the problem of approximating a function in general nonlinear...
In this work a general approach to compute a compressed representation o...
Low-rank tensors are an established framework for high-dimensional
least...
An efficient compression technique based on hierarchical tensors for pop...
We consider best approximation problems in a (nonlinear) subspace
M of a...
We present a novel technique based on deep learning and set theory which...