In this paper we investigate the use of Fourier Neural Operators (FNOs) ...
We propose a novel strategy for Neural Architecture Search (NAS) based o...
We propose a learning framework based on stochastic Bregman iterations t...
Despite the large success of deep neural networks (DNN) in recent years,...
The susceptibility of deep neural networks to untrustworthy predictions,...
The vulnerability of deep neural networks to small and even imperceptibl...
In this work we present an alternative formulation of the higher eigenva...
This paper introduces a new duality theory that generalizes the classica...
In recent years new application areas have emerged in which one aims to
...
In this work we investigate the computation of nonlinear eigenfunctions ...