activity
20172022
most citedExplainable Artificial Intelligence for Exhaust Gas Temperature of Turbofan Engines

8 citations · 9 across the 5 of their papers we have counts for

collaborators

9 papers

cs.NE2022

BBOB Instance Analysis: Landscape Properties and Algorithm Performance across Problem Instances

Fu Xing Long, Diederick Vermetten, Bas van Stein +1

Benchmarking is a key aspect of research into optimization algorithms, and as such the way in which the most popular benchmark suites are designed implicitly guides some parts of a…

cs.LG2022

Deep Learning based pipeline for anomaly detection and quality enhancement in industrial binder jetting processes

Alexander Zeiser, Bas van Stein, Thomas Bäck

Anomaly detection describes methods of finding abnormal states, instances or data points that differ from a normal value space. Industrial processes are a domain where predicitve m…

cs.LG20228 cited

Explainable Artificial Intelligence for Exhaust Gas Temperature of Turbofan Engines

Marios Kefalas, Juan de Santiago Rojo, Asteris Apostolidis +3

Data-driven modeling is an imperative tool in various industrial applications, including many applications in the sectors of aeronautics and commercial aviation. These models are i…

cs.CV2022

Using Machine Learning to Detect Rotational Symmetries from Reflectional Symmetries in 2D Images

Koen Ponse, Anna V. Kononova, Maria Loleyt +1

Automated symmetry detection is still a difficult task in 2021. However, it has applications in computer vision, and it also plays an important part in understanding art. This pape…

cs.NE2021

Emergence of Structural Bias in Differential Evolution

Bas van Stein, Fabio Caraffini, Anna V. Kononova

Heuristic optimisation algorithms are in high demand due to the overwhelming amount of complex optimisation problems that need to be solved. The complexity of these problems is wel…

cs.LG2020

Neural Network Design: Learning from Neural Architecture Search

Bas van Stein, Hao Wang, Thomas Bäck

Neural Architecture Search (NAS) aims to optimize deep neural networks' architecture for better accuracy or smaller computational cost and has recently gained more research interes…