no code implementations • 16 Aug 2023 • Lydia Fischer, Patricia Wollstadt
We therefore propose reject curves that evaluate precision and recall, the recall-reject curve and the precision-reject curve.
no code implementations • 13 Jan 2023 • Felix Lanfermann, Sebastian Schmitt, Patricia Wollstadt
To support the novel understanding of concept identification, we consider a simulated data set from a decision-making problem in the energy management domain and show that the identified clusters are more interpretable with respect to relevant feature subsets than clusters found by common clustering algorithms and are thus more suitable to support a decision maker.
no code implementations • 21 Mar 2022 • Patricia Wollstadt, Daniel L. Rathbun, W. Martin Usrey and, André Moraes Bastos, Michael Lindner, Viola Priesemann, Michael Wibral
We demonstrate our approach by investigating two opposing accounts of predictive coding-like processing strategies, where we quantify the building blocks of predictive coding, namely predictability of inputs and transfer of information, by local active information storage and local transfer entropy.
no code implementations • 10 Dec 2021 • Patricia Wollstadt, Sebastian Schmitt
We thus demonstrate the power of novel information-theoretic approaches in identifying relevant parameters in optimization runs and highlight how these methods avoid the selection of redundant parameters, while detecting interactions that result in synergistic contributions of multiple parameters.
no code implementations • 10 May 2021 • Patricia Wollstadt, Sebastian Schmitt, Michael Wibral
We argue that this lack is inherent to classical information theory which does not provide measures to decompose the information a set of variables provides about a target into unique, redundant, and synergistic contributions.
no code implementations • 21 Dec 2020 • Patricia Wollstadt, Martina Hasenjäger, Christiane B. Wiebel-Herboth
Entropy-based measures are an important tool for studying human gaze behavior under various conditions.
Computational Engineering, Finance, and Science Information Theory Information Theory Quantitative Methods
no code implementations • 10 Mar 2020 • Skylar Sible, Rodrigo Iza-Teran, Jochen Garcke, Nikola Aulig, Patricia Wollstadt
The proposed descriptor provides a novel approach to the parametrization of geometric deformation behavior and enables the use of state-of-the-art data analysis techniques such as machine learning to engineering tasks concerned with plastic deformation behavior.