3 citations · 6 across the 17 of their papers we have counts for
3 papers · 1 filter
Deep Neural Networks and PIDE discretizations
Bastian Bohn, Michael Griebel, Dinesh Kannan
In this paper, we propose neural networks that tackle the problems of stability and field-of-view of a Convolutional Neural Network (CNN). As an alternative to increasing the netwo…
Optimally rotated coordinate systems for adaptive least-squares regression on sparse grids
Bastian Bohn, Michael Griebel, Jens Oettershagen
For low-dimensional data sets with a large amount of data points, standard kernel methods are usually not feasible for regression anymore. Besides simple linear models or involved…
A representer theorem for deep kernel learning
Bastian Bohn, Michael Griebel, Christian Rieger
In this paper we provide a finite-sample and an infinite-sample representer theorem for the concatenation of (linear combinations of) kernel functions of reproducing kernel Hilbert…