Bas van Stein

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 58

Top Topics

Global Optimization

Anomaly Detection

Top Venues

GECCO Companion

Publications

Fu Xing Long, Bas van Stein, Moritz Frenzel, Peter Krause, Markus Gitterle, Thomas Bäck
Generating Cheap Representative Functions for Expensive Automotive Crashworthiness Optimization. ACM Trans. Evol. Learn. Optim. 4 (2) (2024)
Bas van Stein, Diederick Vermetten, Fabio Caraffini, Anna V. Kononova
Deep BIAS: Detecting Structural Bias using Explainable AI. GECCO Companion (2023)
Thomas H. W. Bäck, Anna V. Kononova, Bas van Stein, Hao Wang, Kirill A. Antonov, Roman T. Kalkreuth, Jacob de Nobel, Diederick Vermetten, Roy de Winter, Furong Ye
Evolutionary Algorithms for Parameter Optimization - Thirty Years Later. Evol. Comput. 31 (2) (2023)
Bas van Stein, Fu Xing Long, Moritz Frenzel, Peter Krause, Markus Gitterle, Thomas Bäck
DoE2Vec: Deep-learning Based Features for Exploratory Landscape Analysis. CoRR (2023)
Bas van Stein, Fu Xing Long, Moritz Frenzel, Peter Krause, Markus Gitterle, Thomas Bäck
DoE2Vec: Deep-learning Based Features for Exploratory Landscape Analysis. GECCO Companion (2023)
Alexander Zeiser, Bekir Özcan, Bas van Stein, Thomas Bäck
Evaluation of deep unsupervised anomaly detection methods with a data-centric approach for on-line inspection. Comput. Ind. 146 (2023)
Bas van Stein, Diederick Vermetten, Fabio Caraffini, Anna V. Kononova
Deep-BIAS: Detecting Structural Bias using Explainable AI. CoRR (2023)
Alexander Zeiser, Bekir Özcan, Christoph Kracke, Bas van Stein, Thomas Bäck
A data-centric approach to anomaly detection in layer-based additive manufacturing. Autom. 71 (1) (2023)
Koen Ponse, Anna V. Kononova, Maria Loleyt, Bas van Stein
Using Machine Learning to Detect Rotational Symmetries from Reflectional Symmetries in 2D Images. CoRR (2022)
Diederick Vermetten, Fabio Caraffini, Bas van Stein, Anna V. Kononova
Using structural bias to analyse the behaviour of modular CMA-ES. GECCO Companion (2022)
Bas van Stein, Elena Raponi
GSAreport: Easy to Use Global Sensitivity Reporting. J. Open Source Softw. 7 (78) (2022)
Roy de Winter, Bas van Stein, Thomas Bäck
Multi-point acquisition function for constraint parallel efficient multi-objective optimization. GECCO (2022)
Marios Kefalas, Juan de Santiago Rojo Jr., Asteris Apostolidis, Dirk van den Herik, Bas van Stein, Thomas Bäck
Explainable Artificial Intelligence for Exhaust Gas Temperature of Turbofan Engines. J. Aerosp. Inf. Syst. 19 (6) (2022)
Fu Xing Long, Bas van Stein, Moritz Frenzel, Peter Krause, Markus Gitterle, Thomas Bäck
Learning the characteristics of engineering optimization problems with applications in automotive crash. GECCO (2022)
Thiago Rios, Bas van Stein, Thomas Bäck, Bernhard Sendhoff, Stefan Menzel
Multitask Shape Optimization Using a 3-D Point Cloud Autoencoder as Unified Representation. IEEE Trans. Evol. Comput. 26 (2) (2022)
Qi Huang, Roy de Winter, Bas van Stein, Thomas Bäck, Anna V. Kononova
Multi-surrogate Assisted Efficient Global Optimization for Discrete Problems. CoRR (2022)
Fu Xing Long, Diederick Vermetten, Bas van Stein, Anna V. Kononova
BBOB Instance Analysis: Landscape Properties and Algorithm Performance across Problem Instances. CoRR (2022)
Bas van Stein, Elena Raponi, Zahra Sadeghi, Niek Bouman, Roeland C. H. J. Van Ham, Thomas Bäck
A Comparison of Global Sensitivity Analysis Methods for Explainable AI With an Application in Genomic Prediction. IEEE Access 10 (2022)
Diederick Vermetten, Bas van Stein, Fabio Caraffini, Leandro L. Minku, Anna V. Kononova
BIAS: A Toolbox for Benchmarking Structural Bias in the Continuous Domain. IEEE Trans. Evol. Comput. 26 (6) (2022)
Qi Huang, Roy de Winter, Bas van Stein, Thomas Bäck, Anna V. Kononova
Multi-surrogate Assisted Efficient Global Optimization for Discrete Problems. SSCI (2022)
Marios Kefalas, Juan de Santiago Rojo Jr., Asteris Apostolidis, Dirk van den Herik, Bas van Stein, Thomas Bäck
Explainable Artificial Intelligence for Exhaust Gas Temperature of Turbofan Engines. CoRR (2022)
Alexander Zeiser, Bas van Stein, Thomas Bäck
Deep Learning based pipeline for anomaly detection and quality enhancement in industrial binder jetting processes. CoRR (2022)
Roy de Winter, Philip Bronkhorst, Bas van Stein, Thomas Bäck
Constrained Multi-Objective Optimization with a Limited Budget of Function Evaluations. Memetic Comput. 14 (2) (2022)
Bas van Stein, Fabio Caraffini, Anna V. Kononova
Emergence of Structural Bias in Differential Evolution. CoRR (2021)
Sneha Saha, Thiago Rios, Leandro L. Minku, Bas van Stein, Patricia Wollstadt, Xin Yao, Thomas Bäck, Bernhard Sendhoff, Stefan Menzel
Exploiting Generative Models for Performance Predictions of 3D Car Designs. SSCI (2021)
Roy de Winter, Bas van Stein, Thomas Bäck
SAMO-COBRA: A Fast Surrogate Assisted Constrained Multi-objective Optimization Algorithm. EMO (2021)
Thiago Rios, Bas van Stein, Patricia Wollstadt, Thomas Bäck, Bernhard Sendhoff, Stefan Menzel
Exploiting Local Geometric Features in Vehicle Design Optimization with 3D Point Cloud Autoencoders. CEC (2021)
Koen Ponse, Anna V. Kononova, Maria Loleyt, Bas van Stein
Using Machine Learning to Detect Rotational Symmetries from Reflectional Symmetries in 2D Images. SSCI (2021)
Gideon Hanse, Roy de Winter, Bas van Stein, Thomas Bäck
Optimally Weighted Ensembles for Efficient Multi-objective Optimization. LOD (2021)
Alexander Zeiser, Bas van Stein, Thomas Bäck
Requirements towards optimizing analytics in industrial processes. ANT/EDI40 (2021)
Bas van Stein, Fabio Caraffini, Anna V. Kononova
Emergence of structural bias in differential evolution. GECCO Companion (2021)
Thiago Rios, Bas van Stein, Thomas Bäck, Bernhard Sendhoff, Stefan Menzel
Point2FFD: Learning Shape Representations of Simulation-Ready 3D Models for Engineering Design Optimization. 3DV (2021)
Thiago Rios, Bas van Stein, Stefan Menzel, Thomas Bäck, Bernhard Sendhoff, Patricia Wollstadt
Feature Visualization for 3D Point Cloud Autoencoders. IJCNN (2020)
Thiago Rios, Jiawen Kong, Bas van Stein, Thomas Bäck, Patricia Wollstadt, Bernhard Sendhoff, Stefan Menzel
Back To Meshes: Optimal Simulation-ready Mesh Prototypes For Autoencoder-based 3D Car Point Clouds. SSCI (2020)
Yali Wang, Bas van Stein, Michael T. M. Emmerich, Thomas Bäck
A Tailored NSGA-III Instantiation for Flexible Job Shop Scheduling. CoRR (2020)
Bas van Stein, Hao Wang, Thomas Bäck
Neural Network Design: Learning from Neural Architecture Search. CoRR (2020)
Bas van Stein, Hao Wang, Wojtek Kowalczyk, Michael Emmerich, Thomas Bäck
Cluster-based Kriging approximation algorithms for complexity reduction. Appl. Intell. 50 (3) (2020)
Yali Wang, Bas van Stein, Thomas Bäck, Michael Emmerich
A Tailored NSGA-III for Multi-objective Flexible Job Shop Scheduling. SSCI (2020)
Yali Wang, Bas van Stein, Thomas Bäck, Michael Emmerich
Improving NSGA-III for flexible job shop scheduling using automatic configuration, smart initialization and local search. GECCO Companion (2020)
Bas van Stein, Hao Wang, Thomas Bäck
Neural Network Design: Learning from Neural Architecture Search. SSCI (2020)
Xin Guo, Bas van Stein, Thomas Bäck
A New Approach Towards the Combined Algorithm Selection and Hyper-parameter Optimization Problem. SSCI (2019)
Thiago Rios, Patricia Wollstadt, Bas van Stein, Thomas Bäck, Zhao Xu, Bernhard Sendhoff, Stefan Menzel
Scalability of Learning Tasks on 3D CAE Models Using Point Cloud Autoencoders. SSCI (2019)
Bas van Stein, Hao Wang, Thomas Bäck
Automatic Configuration of Deep Neural Networks with Parallel Efficient Global Optimization. IJCNN (2019)
Thiago Rios, Bernhard Sendhoff, Stefan Menzel, Thomas Bäck, Bas van Stein
On the Efficiency of a Point Cloud Autoencoder as a Geometric Representation for Shape Optimization. SSCI (2019)
Bas van Stein, Hao Wang, Wojtek Kowalczyk, Thomas Bäck
A Novel Uncertainty Quantification Method for Efficient Global Optimization. IPMU (3) (2018)
Bas van Stein, Hao Wang, Thomas Bäck
Automatic Configuration of Deep Neural Networks with EGO. CoRR (2018)
Roy de Winter, Bas van Stein, Matthys Dijkman, Thomas Bäck
Designing Ships Using Constrained Multi-objective Efficient Global Optimization. LOD (2018)
Bas van Stein, Hao Wang, Wojtek Kowalczyk, Michael T. M. Emmerich, Thomas Bäck
Cluster-based Kriging Approximation Algorithms for Complexity Reduction. CoRR (2017)
Hao Wang, Bas van Stein, Michael Emmerich, Thomas Bäck
A new acquisition function for Bayesian optimization based on the moment-generating function. SMC (2017)
Sander van Rijn, Hao Wang, Bas van Stein, Thomas Bäck
Algorithm configuration data mining for CMA evolution strategies. GECCO (2017)
Hao Wang, Bas van Stein, Michael T. M. Emmerich, Thomas Bäck
Time complexity reduction in efficient global optimization using cluster kriging. GECCO (2017)
Thierry van der Spek, Bas van Stein, Marcel van der Holst, Thomas Bäck
A multi-method simulation of a high-frequency bus line. ITSC (2017)
Bas van Stein, Matthijs van Leeuwen, Thomas Bäck
Local subspace-based outlier detection using global neighbourhoods. IEEE BigData (2016)
Bas van Stein, Hao Wang, Wojtek Kowalczyk, Michael T. M. Emmerich, Thomas Bäck
Fuzzy clustering for Optimally Weighted Cluster Kriging. FUZZ-IEEE (2016)
Bas van Stein, Wojtek Kowalczyk
An Incremental Algorithm for Repairing Training Sets with Missing Values. IPMU (2) (2016)
Bas van Stein, Matthijs van Leeuwen, Thomas Bäck
Local Subspace-Based Outlier Detection using Global Neighbourhoods. CoRR (2016)
Bas van Stein, Wojtek Kowalczyk, Thomas Bäck
Analysis and Visualization of Missing Value Patterns. IPMU (2) (2016)
Pepijn Van Heiningen, Bas van Stein, Thomas Bäck
A framework for evaluating meta-models for simulation-based optimisation. SSCI (2016)
Bas van Stein, Hao Wang, Wojtek Kowalczyk, Thomas Bäck, Michael Emmerich
Optimally Weighted Cluster Kriging for Big Data Regression. IDA (2015)
Fu Xing Long, Diederick Vermetten, Bas van Stein, Anna V. Kononova
BBOB Instance Analysis: Landscape Properties and Algorithm Performance Across Problem Instances. EvoApplications@EvoStar (2013)