Optimally Weighted Cluster Kriging for Big Data Regression. - Bas van Stein; Hao Wang 025; Wojtek Kowalczyk; Thomas Bäck; Michael Emmerich 001 (IDA, 2015)

Local subspace-based outlier detection using global neighbourhoods. - Bas van Stein; Matthijs van Leeuwen; Thomas Bäck (IEEE BigData, 2016)

Fuzzy clustering for Optimally Weighted Cluster Kriging. - Bas van Stein; Hao Wang 025; Wojtek Kowalczyk; Michael T. M. Emmerich; Thomas Bäck (FUZZ-IEEE, 2016)

An Incremental Algorithm for Repairing Training Sets with Missing Values. - Bas van Stein; Wojtek Kowalczyk (IPMU (2), 2016)

Analysis and Visualization of Missing Value Patterns. - Bas van Stein; Wojtek Kowalczyk; Thomas Bäck (IPMU (2), 2016)

A framework for evaluating meta-models for simulation-based optimisation. - Pepijn Van Heiningen; Bas van Stein; Thomas Bäck (SSCI, 2016)

Time complexity reduction in efficient global optimization using cluster kriging. - Hao Wang 025; Bas van Stein; Michael T. M. Emmerich; Thomas Bäck (GECCO, 2017)

Algorithm configuration data mining for CMA evolution strategies. - Sander van Rijn; Hao Wang 025; Bas van Stein; Thomas Bäck (GECCO, 2017)

A multi-method simulation of a high-frequency bus line. - Thierry van der Spek; Bas van Stein; Marcel van der Holst; Thomas Bäck (ITSC, 2017)

A new acquisition function for Bayesian optimization based on the moment-generating function. - Hao Wang 025; Bas van Stein; Michael Emmerich 001; Thomas Bäck (SMC, 2017)

A Novel Uncertainty Quantification Method for Efficient Global Optimization. - Bas van Stein; Hao Wang 025; Wojtek Kowalczyk; Thomas Bäck (IPMU (3), 2018)

Designing Ships Using Constrained Multi-objective Efficient Global Optimization. - Roy de Winter; Bas van Stein; Matthys Dijkman; Thomas Bäck (LOD, 2018)

Automatic Configuration of Deep Neural Networks with EGO. - Bas van Stein; Hao Wang 025; Thomas Bäck (CoRR, 2018)

Automatic Configuration of Deep Neural Networks with Parallel Efficient Global Optimization. - Bas van Stein; Hao Wang 025; Thomas Bäck (IJCNN, 2019)

A New Approach Towards the Combined Algorithm Selection and Hyper-parameter Optimization Problem. - Xin Guo; Bas van Stein; Thomas Bäck (SSCI, 2019)

On the Efficiency of a Point Cloud Autoencoder as a Geometric Representation for Shape Optimization. - Thiago Rios; Bernhard Sendhoff; Stefan Menzel; Thomas Bäck; Bas van Stein (SSCI, 2019)

Scalability of Learning Tasks on 3D CAE Models Using Point Cloud Autoencoders. - Thiago Rios; Patricia Wollstadt; Bas van Stein; Thomas Bäck; Zhao Xu 001; Bernhard Sendhoff; Stefan Menzel (SSCI, 2019)

Improving NSGA-III for flexible job shop scheduling using automatic configuration, smart initialization and local search. - Yali Wang 002; Bas van Stein; Thomas Bäck; Michael Emmerich 001 (GECCO Companion, 2020)

Feature Visualization for 3D Point Cloud Autoencoders. - Thiago Rios; Bas van Stein; Stefan Menzel; Thomas Bäck; Bernhard Sendhoff; Patricia Wollstadt (IJCNN, 2020)

Back To Meshes: Optimal Simulation-ready Mesh Prototypes For Autoencoder-based 3D Car Point Clouds. - Thiago Rios; Jiawen Kong; Bas van Stein; Thomas Bäck; Patricia Wollstadt; Bernhard Sendhoff; Stefan Menzel (SSCI, 2020)

Neural Network Design: Learning from Neural Architecture Search. - Bas van Stein; Hao Wang 025; Thomas Bäck (SSCI, 2020)

A Tailored NSGA-III for Multi-objective Flexible Job Shop Scheduling. - Yali Wang 002; Bas van Stein; Thomas Bäck; Michael Emmerich 001 (SSCI, 2020)

Cluster-based Kriging approximation algorithms for complexity reduction. - Bas van Stein; Hao Wang 025; Wojtek Kowalczyk; Michael Emmerich 001; Thomas Bäck (Appl. Intell., 2020)

A Tailored NSGA-III Instantiation for Flexible Job Shop Scheduling. - Yali Wang 002; Bas van Stein; Michael T. M. Emmerich; Thomas Bäck (CoRR, 2020)

Point2FFD: Learning Shape Representations of Simulation-Ready 3D Models for Engineering Design Optimization. - Thiago Rios; Bas van Stein; Thomas Bäck; Bernhard Sendhoff; Stefan Menzel (3DV, 2021)

Requirements towards optimizing analytics in industrial processes. - Alexander Zeiser; Bas van Stein; Thomas Bäck (ANT/EDI40, 2021)

Exploiting Local Geometric Features in Vehicle Design Optimization with 3D Point Cloud Autoencoders. - Thiago Rios; Bas van Stein; Patricia Wollstadt; Thomas Bäck; Bernhard Sendhoff; Stefan Menzel (CEC, 2021)

SAMO-COBRA: A Fast Surrogate Assisted Constrained Multi-objective Optimization Algorithm. - Roy de Winter; Bas van Stein; Thomas Bäck (EMO, 2021)

Emergence of structural bias in differential evolution. - Bas van Stein; Fabio Caraffini; Anna V. Kononova (GECCO Companion, 2021)

Optimally Weighted Ensembles for Efficient Multi-objective Optimization. - Gideon Hanse; Roy de Winter; Bas van Stein; Thomas Bäck (LOD, 2021)

Using Machine Learning to Detect Rotational Symmetries from Reflectional Symmetries in 2D Images. - Koen Ponse; Anna V. Kononova; Maria Loleyt; Bas van Stein (SSCI, 2021)

Exploiting Generative Models for Performance Predictions of 3D Car Designs. - Sneha Saha; Thiago Rios; Leandro L. Minku; Bas van Stein; Patricia Wollstadt; Xin Yao 001; Thomas Bäck; Bernhard Sendhoff; Stefan Menzel (SSCI, 2021)

Learning the characteristics of engineering optimization problems with applications in automotive crash. - Fu Xing Long; Bas van Stein; Moritz Frenzel; Peter Krause 001; Markus Gitterle; Thomas Bäck (GECCO, 2022)

Using structural bias to analyse the behaviour of modular CMA-ES. - Diederick Vermetten; Fabio Caraffini; Bas van Stein; Anna V. Kononova (GECCO Companion, 2022)

Multi-point acquisition function for constraint parallel efficient multi-objective optimization. - Roy de Winter; Bas van Stein; Thomas Bäck (GECCO, 2022)

Multi-surrogate Assisted Efficient Global Optimization for Discrete Problems. - Qi Huang; Roy de Winter; Bas van Stein; Thomas Bäck; Anna V. Kononova (SSCI, 2022)

A Comparison of Global Sensitivity Analysis Methods for Explainable AI With an Application in Genomic Prediction. - Bas van Stein; Elena Raponi; Zahra Sadeghi; Niek Bouman; Roeland C. H. J. van Ham; Thomas Bäck (IEEE Access, 2022)

Deep Learning based pipeline for anomaly detection and quality enhancement in industrial binder jetting processes. - Alexander Zeiser; Bas van Stein; Thomas Bäck (CoRR, 2022)

Constrained Multi-Objective Optimization with a Limited Budget of Function Evaluations. - Roy de Winter; Philip Bronkhorst; Bas van Stein; Thomas Bäck (Memetic Comput., 2022)

Multitask Shape Optimization Using a 3-D Point Cloud Autoencoder as Unified Representation. - Thiago Rios; Bas van Stein; Thomas Bäck; Bernhard Sendhoff; Stefan Menzel (IEEE Trans. Evol. Comput., 2022)

BIAS: A Toolbox for Benchmarking Structural Bias in the Continuous Domain. - Diederick Vermetten; Bas van Stein; Fabio Caraffini; Leandro L. Minku; Anna V. Kononova (IEEE Trans. Evol. Comput., 2022)

Explainable Artificial Intelligence for Exhaust Gas Temperature of Turbofan Engines. - Marios Kefalas; Juan de Santiago Rojo Jr.; Asteris Apostolidis; Dirk van den Herik; Bas van Stein; Thomas Bäck (J. Aerosp. Inf. Syst., 2022)

GSAreport: Easy to Use Global Sensitivity Reporting. - Bas van Stein; Elena Raponi (J. Open Source Softw., 2022)

BBOB Instance Analysis: Landscape Properties and Algorithm Performance Across Problem Instances. - Fu Xing Long; Diederick Vermetten; Bas van Stein; Anna V. Kononova (EvoApplications@EvoStar, 2023)

Curing ill-Conditionality via Representation-Agnostic Distance-Driven Perturbations. - Kirill A. Antonov; Anna V. Kononova; Thomas Bäck; Niki van Stein (FOGA, 2023)

DoE2Vec: Deep-learning Based Features for Exploratory Landscape Analysis. - Bas van Stein; Fu Xing Long; Moritz Frenzel; Peter Krause 001; Markus Gitterle; Thomas Bäck (GECCO Companion, 2023)

Deep BIAS: Detecting Structural Bias using Explainable AI. - Bas van Stein; Diederick Vermetten; Fabio Caraffini; Anna V. Kononova (GECCO Companion, 2023)

Clustering-based Domain-Incremental Learning. - Christiaan Lamers; René Vidal; Nabil Belbachir; Niki van Stein; Thomas Bäck; Paris Giampouras (ICCV (Workshops), 2023)

Challenges of ELA-Guided Function Evolution Using Genetic Programming. - Fu Xing Long; Diederick Vermetten; Anna V. Kononova; Roman Kalkreuth; Kaifeng Yang; Thomas Bäck; Niki van Stein (IJCCI, 2023)

The Opaque Nature of Intelligence and the Pursuit of Explainable AI. - Sarah L. Thomson; Niki van Stein; Daan van den Berg; Cees van Leeuwen (IJCCI, 2023)

A data-centric approach to anomaly detection in layer-based additive manufacturing. - Alexander Zeiser; Bekir Özcan; Christoph Kracke; Bas van Stein; Thomas Bäck (Autom., 2023)

Representation-agnostic distance-driven perturbation for optimizing ill-conditioned problems. - Kirill Antonov; Anna V. Kononova; Thomas Bäck; Niki van Stein (CoRR, 2023)

Evolutionary Algorithms for Parameter Optimization - Thirty Years Later. - Thomas H. W. Bäck; Anna V. Kononova; Bas van Stein; Hao Wang 025; Kirill A. Antonov; Roman T. Kalkreuth; Jacob de Nobel; Diederick Vermetten; Roy de Winter; Furong Ye (Evol. Comput., 2023)

Evaluation of deep unsupervised anomaly detection methods with a data-centric approach for on-line inspection. - Alexander Zeiser; Bekir Özcan; Bas van Stein; Thomas Bäck (Comput. Ind., 2023)

Challenges of ELA-based Function Evolution using Genetic Programming - Reproducability files. - Fu Xing Long; Diederick Vermetten; Anna V. Kononova; Roman Kalkreuth; Kaifeng Yang; Thomas Bäck; Niki van Stein (Zenodo, 2023)

TX-Gen: Multi-Objective Optimization for Sparse Counterfactual Explanations for Time-Series Classification. - Qi Huang; Sofoklis Kitharidis; Thomas Bäck; Niki van Stein (EXPLAINS, 2024)

A Functional Analysis Approach to Symbolic Regression. - Kirill Antonov; Roman Kalkreuth; Kaifeng Yang; Thomas Bäck; Niki van Stein; Anna V. Kononova (GECCO, 2024)

A Critical Analysis of Raven Roost Optimization. - Martijn Halsema; Diederick Vermetten; Thomas Bäck; Niki van Stein (GECCO Companion, 2024)

A Corridor Model Evolutionary Algorithm for Fast Converging Green Vehicle Routing Problem. - Ananta Shahane; Niki van Stein; Yingjie Fan 002 (GECCO Companion, 2024)

Modular Optimization Framework for Mixed Expensive and Inexpensive Real-World Problems. - Roy de Winter; Thomas Bäck; Niki van Stein (GECCO Companion, 2024)

Hot off the Press: Parallel Multi-Objective Optimization for Expensive and Inexpensive Objectives and Constraints. - Roy de Winter; Bas Milatz; Julian Blank; Niki van Stein; Thomas Bäck; Kalyanmoy Deb (GECCO Companion, 2024)

Towards Fairness in Machine Learning: Balancing Racially Imbalanced Datasets Through Data Augmentation and Generative AI. - Anthonie Schaap; Sofoklis Kitharidis; Niki van Stein (IJCCI, 2024)

ACO-NSGAII: A Novel Metaheuristics for Bi-Objective Electric Vehicle Routing Problems. - Suzan Al-Nassar; Niki van Stein; Yingjie Fan 002 (ITSC, 2024)

Landscape-Aware Automated Algorithm Configuration Using Multi-output Mixed Regression and Classification. - Fu Xing Long; Moritz Frenzel; Peter Krause 001; Markus Gitterle; Thomas Bäck; Niki van Stein (PPSN (2), 2024)

A Deep Dive Into Effects of Structural Bias on CMA-ES Performance Along Affine Trajectories. - Niki van Stein; Sarah L. Thomson; Anna V. Kononova (PPSN (2), 2024)

Beyond the Veil of Similarity: Quantifying Semantic Continuity in Explainable AI. - Qi Huang; Emanuele Mezzi; Osman Mutlu; Miltiadis Kofinas; Vidya Prasad; Shadnan Azwad Khan; Elena Ranguelova; Niki van Stein (xAI (1), 2024)

Shapelet-based Model-agnostic Counterfactual Local Explanations for Time Series Classification. - Qi Huang; Wei Chen 072; Thomas Bäck; Niki van Stein (CoRR, 2024)

Automated Federated Learning via Informed Pruning. - Christian Internò; Elena Raponi; Niki van Stein; Thomas Bäck; Markus Olhofer; Yaochu Jin; Barbara Hammer (CoRR, 2024)

A Survey of Meta-features Used for Automated Selection of Algorithms for Black-box Single-objective Continuous Optimization. - Gjorgjina Cenikj; Ana Nikolikj; Gasper Petelin; Niki van Stein; Carola Doerr; Tome Eftimov (CoRR, 2024)

Evolutionary Computation and Explainable AI: A Roadmap to Transparent Intelligent Systems. - Ryan Zhou; Jaume Bacardit; Alexander E. I. Brownlee; Stefano Cagnoni; Martin Fyvie; Giovanni Iacca; John A. W. McCall; Niki van Stein; David Walker 003; Ting Hu 001 (CoRR, 2024)

Reasoning with Large Language Models, a Survey. - Aske Plaat; Annie Wong; Suzan Verberne; Joost Broekens; Niki van Stein; Thomas Bäck (CoRR, 2024)

Selection of Filters for Photonic Crystal Spectrometer Using Domain-Aware Evolutionary Algorithms. - Kirill A. Antonov; Marijn Siemons; Niki van Stein; Thomas H. W. Bäck; Ralf Kohlhaas; Anna V. Kononova (CoRR, 2024)

In-the-loop Hyper-Parameter Optimization for LLM-Based Automated Design of Heuristics. - Niki van Stein; Diederick Vermetten; Thomas Bäck (CoRR, 2024)

Parallel multi-objective optimization for expensive and inexpensive objectives and constraints. - Roy de Winter; Bas Milatz; Julian Blank; Niki van Stein; Thomas Bäck; Kalyanmoy Deb (Swarm Evol. Comput., 2024)

Generating Cheap Representative Functions for Expensive Automotive Crashworthiness Optimization. - Fu Xing Long; Bas van Stein; Moritz Frenzel; Peter Krause 001; Markus Gitterle; Thomas Bäck (ACM Trans. Evol. Learn. Optim., 2024)

LLaMEA. - Niki van Stein; Thomas Bäck (Zenodo, 2024)

IOH-Xplainer - code, experiments and results. - Niki van Stein; Diederick Vermetten; Anna V. Kononova; Thomas Bäck (Zenodo, 2024)

Stalling in Space: Attractor Analysis for Any Algorithm. - Sarah L. Thomson; Quentin Renau; Diederick Vermetten; Emma Hart; Niki van Stein; Anna V. Kononova (EvoApplications (2), 2025)

Controlling the Mutation in Large Language Models for the Efficient Evolution of Algorithms. - Haoran Yin; Anna V. Kononova; Thomas Bäck; Niki van Stein (EvoApplications (2), 2025)

Code Evolution Graphs: Understanding Large Language Model Driven Design of Algorithms. - Niki van Stein; Anna V. Kononova; Lars Kotthoff; Thomas Bäck (GECCO, 2025)

EconoJax: A Fast & Scalable Economic Simulation in JAX. - Koen Ponse; Aske Plaat; Niki van Stein; Thomas M. Moerland (AAMAS, 2025)

Diffusion Models for Tabular Data: Challenges, Current Progress, and Future Directions. - Zhong Li 002; Qi Huang; Lincen Yang; Jiayang Shi; Zhao Yang; Niki van Stein; Thomas Bäck; Matthijs van Leeuwen (CoRR, 2025)

Optimizing Photonic Structures with Large Language Model Driven Algorithm Discovery. - Haoran Yin; Anna V. Kononova; Thomas Bäck; Niki van Stein (CoRR, 2025)

Agentic Large Language Models, a survey. - Aske Plaat; Max J. van Duijn; Niki van Stein; Mike Preuss; Peter van der Putten; Kees Joost Batenburg (CoRR, 2025)

BLADE: Benchmark suite for LLM-driven Automated Design and Evolution of iterative optimisation heuristics. - Niki van Stein; Anna V. Kononova; Haoran Yin; Thomas Bäck (CoRR, 2025)

LLaMEA: A Large Language Model Evolutionary Algorithm for Automatically Generating Metaheuristics. - Niki van Stein; Thomas Bäck (IEEE Trans. Evol. Comput., 2025)

Why Are You Wrong? Counterfactual Explanations for Language Grounding with 3D Objects. - Tobias Preintner; Weixuan Yuan; Qi Huang; Adrian König; Thomas Bäck; Elena Raponi; Niki van Stein (CoRR, 2025)

Towards a Deeper Understanding of Reasoning Capabilities in Large Language Models. - Annie Wong; Thomas Bäck; Aske Plaat; Niki van Stein; Anna V. Kononova (CoRR, 2025)

Evolutionary Computation and Large Language Models: A Survey of Methods, Synergies, and Applications. - Dikshit Chauhan; Bapi Dutta; Indu Bala; Niki van Stein; Thomas Bäck; Anupam Yadav (CoRR, 2025)

LLaMEA-BO: A Large Language Model Evolutionary Algorithm for Automatically Generating Bayesian Optimization Algorithms. - Wenhu Li; Niki van Stein; Thomas Bäck; Elena Raponi (CoRR, 2025)

Leveraging Lightweight Generators for Memory Efficient Continual Learning. - Christiaan Lamers; Ahmed Nabil Belbachir; Thomas Bäck; Niki van Stein (CoRR, 2025)

Explainable Benchmarking for Iterative Optimization Heuristics. - Niki van Stein; Diederick Vermetten; Anna V. Kononova; Thomas Bäck (ACM Trans. Evol. Learn. Optim., 2025)

Behaviour Space Analysis of LLM-driven Meta-heuristic Discovery. - Niki van Stein; Haoran Yin; Anna V. Kononova; Thomas Bäck; Gabriela Ochoa (CoRR, 2025)

How does Chain of Thought Think? Mechanistic Interpretability of Chain-of-Thought Reasoning with Sparse Autoencoding. - Xi Chen; Aske Plaat; Niki van Stein (CoRR, 2025)