984 citations · 999 across the 13 of their papers we have counts for
20 papers
Mixture of Decision Trees for Interpretable Machine Learning
Simeon Brüggenjürgen, Nina Schaaf, Pascal Kerschke +1
This work introduces a novel interpretable machine learning method called Mixture of Decision Trees (MoDT). It constitutes a special case of the Mixture of Experts ensemble archite…
Kalman-Bucy-Informed Neural Network for System Identification
Tobias Nagel, Marco F. Huber
Identifying parameters in a system of nonlinear, ordinary differential equations is vital for designing a robust controller. However, if the system is stochastic in its nature or i…
Simplified Learning of CAD Features Leveraging a Deep Residual Autoencoder
Raoul Schönhof, Jannes Elstner, Radu Manea +3
In the domain of computer vision, deep residual neural networks like EfficientNet have set new standards in terms of robustness and accuracy. One key problem underlying the trainin…
Feature Visualization within an Automated Design Assessment leveraging Explainable Artificial Intelligence Methods
Raoul Schönhof, Artem Werner, Jannes Elstner +3
Not only automation of manufacturing processes but also automation of automation procedures itself become increasingly relevant to automation research. In this context, automated c…
A MIMO Radar-Based Metric Learning Approach for Activity Recognition
Fady Aziz, Omar Metwally, Pascal Weller +2
Human activity recognition is seen of great importance in the medical and surveillance fields. Radar has shown great feasibility for this field based on the captured micro-Doppler…
Precise Object Placement with Pose Distance Estimations for Different Objects and Grippers
Kilian Kleeberger, Jonathan Schnitzler, Muhammad Usman Khalid +3
This paper introduces a novel approach for the grasping and precise placement of various known rigid objects using multiple grippers within highly cluttered scenes. Using a single…