research
∙
07/13/2023
Implicit regularization in AI meets generalized hardness of approximation in optimization – Sharp results for diagonal linear networks
Understanding the implicit regularization imposed by neural network arch...
share
research
∙
06/01/2021
Recovering wavelet coefficients from binary samples using fast transforms
Recovering a signal (function) from finitely many binary or Fourier samp...
research
∙
01/20/2021
Can stable and accurate neural networks be computed? – On the barriers of deep learning and Smale's 18th problem
Deep learning (DL) has had unprecedented success and is now entering sci...
research
∙
01/05/2020
The troublesome kernel: why deep learning for inverse problems is typically unstable
There is overwhelming empirical evidence that Deep Learning (DL) leads t...
research
∙
06/04/2019
What do AI algorithms actually learn? - On false structures in deep learning
There are two big unsolved mathematical questions in artificial intellig...
research
∙
04/30/2019
Uniform recovery in infinite-dimensional compressed sensing and applications to structured binary sampling
Infinite-dimensional compressed sensing deals with the recovery of analo...
research
∙
02/14/2019
