5 papers
Including Sparse Production Knowledge into Variational Autoencoders to Increase Anomaly Detection Reliability
Tom Hammerbacher, Markus Lange-Hegermann, Gorden Platz
Digitalization leads to data transparency for production systems that we can benefit from with data-driven analysis methods like neural networks. For example, automated anomaly det…
Singularities of Algebraic Differential Equations
Markus Lange-Hegermann, Daniel Robertz, Werner M. Seiler +1
There exists a well established differential topological theory of singularities of ordinary differential equations. It has mainly studied scalar equations of low order. We propose…
Linearly Constrained Gaussian Processes with Boundary Conditions
Markus Lange-Hegermann
One goal in Bayesian machine learning is to encode prior knowledge into prior distributions, to model data efficiently. We consider prior knowledge from systems of linear partial d…
Thomas Decomposition and Nonlinear Control Systems
Markus Lange-Hegermann, Daniel Robertz
This paper applies the Thomas decomposition technique to nonlinear control systems, in particular to the study of the dependence of the system behavior on parameters. Thomas' algor…
Thomas decompositions of parametric nonlinear control systems
Markus Lange-Hegermann, Daniel Robertz
This paper presents an algorithmic method to study structural properties of nonlinear control systems in dependence of parameters. The result consists of a description of parameter…