Promises and pitfalls of deep neural networks in neuroimaging-based psychiatric research

no code implementations • 20 Jan 2023 • Fabian Eitel, Marc-André Schulz, Moritz Seiler, Henrik Walter, Kerstin Ritter

By promising more accurate diagnostics and individual treatment recommendations, deep neural networks and in particular convolutional neural networks have advanced to a powerful tool in medical imaging.

Transfer Learning

Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem

1 code implementation • 29 Jun 2020 • Moritz Seiler, Janina Pohl, Jakob Bossek, Pascal Kerschke, Heike Trautmann

In this work we focus on the well-known Euclidean Traveling Salesperson Problem (TSP) and two highly competitive inexact heuristic TSP solvers, EAX and LKH, in the context of per-instance algorithm selection (AS).

feature selection

Enhancing Resilience of Deep Learning Networks by Means of Transferable Adversaries

no code implementations • 27 May 2020 • Moritz Seiler, Heike Trautmann, Pascal Kerschke

Artificial neural networks in general and deep learning networks in particular established themselves as popular and powerful machine learning algorithms.