activity
20122020
most citedExplainable Artificial Intelligence and Machine Learning: A reality rooted perspective

107 citations · 185 across the 7 of their papers we have counts for

collaborators

8 papers

cs.AI2020★ 66 cited

A clarification of misconceptions, myths and desired status of artificial intelligence

Frank Emmert-Streib, Olli Yli-Harja, Matthias Dehmer

The field artificial intelligence (AI) has been founded over 65 years ago. Starting with great hopes and ambitious goals the field progressed though various stages of popularity an…

cs.SE2020

Ensuring the Robustness and Reliability of Data-Driven Knowledge Discovery Models in Production and Manufacturing

Shailesh Tripathi, David Muhr, Brunner Manuel +3

The implementation of robust, stable, and user-centered data analytics and machine learning models is confronted by numerous challenges in production and manufacturing. Therefore,…

cs.AI2020★ 107 cited

Explainable Artificial Intelligence and Machine Learning: A reality rooted perspective

Frank Emmert-Streib, Olli Yli-Harja, Matthias Dehmer

We are used to the availability of big data generated in nearly all fields of science as a consequence of technological progress. However, the analysis of such data possess vast ch…

math.CO2019

On conjectures of network distance measures by using graph spectra

Aleksandar Ilic, Matthias Dehmer

In this note we resolve three conjectures from [M. Dehmer, S. Pickl, Y. Shi, G. Yu, \emph{New inequalities for network distance measures by using graph spectra}, Discrete Appl. Mat…

cs.SI2017

Quantitative Graph Theory: A new branch of graph theory and in network science

Matthias Dehmer, Frank Emmert-Streib, Yongtang Shi

In this paper, we describe {\sc quantitative graph theory} and argue it is a new graph-theoretical branch in network science, however, with significant different features compared…

q-fin.CP2017

Computational Analysis of the structural properties of Economic and Financial Networks

Frank Emmert-Streib, Aliyu Musa, Kestutis Baltakys +5

In recent years, methods from network science are gaining rapidly interest in economics and finance. A reason for this is that in a globalized world the interconnectedness among ec…

math.CO2014★ 3 cited

Novel Inequalities for Generalized Graph Entropies Revisited, Graph Energies and Topological Indices

Xueliang Li, Zhongmei Qin, Meiqin Wei +2

The entropy of a graph is an information-theoretic quantity which expresses the complexity of a graph \cite{DM1,M}. After Shannon introduced the definition of entropy to informatio…

cs.IT2012★ 9 cited

Information inequalities and Generalized Graph Entropies

Lavanya Sivakumar, Matthias Dehmer

In this article, we discuss the problem of establishing relations between information measures assessed for network structures. Two types of entropy based measures namely, the Shan…