Stefan Menzel

Orcid: 0000-0001-7594-2308

According to our database1, Stefan Menzel authored at least 95 papers between 2006 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Knowledge Transfer for Dynamic Multi-Objective Optimization With a Changing Number of Objectives.
IEEE Trans. Emerg. Top. Comput. Intell., December, 2024

LLM2FEA: Discover Novel Designs with Generative Evolutionary Multitasking.
CoRR, 2024

Generative AI-based Prompt Evolution Engineering Design Optimization With Vision-Language Model.
CoRR, 2024

Prompt Evolutionary Design Optimization with Generative Shape and Vision-Language models.
Proceedings of the IEEE Congress on Evolutionary Computation, 2024

2023
Generating and Adapting to Diverse Ad Hoc Partners in Hanabi.
IEEE Trans. Games, June, 2023

Evaluation of geometric similarity metrics for structural clusters generated using topology optimization.
Appl. Intell., 2023

Large Language and Text-to-3D Models for Engineering Design Optimization.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023

2022
CarHoods10k: An Industry-Grade Data Set for Representation Learning and Design Optimization in Engineering Applications.
IEEE Trans. Evol. Comput., 2022

A Novel Generalized Metaheuristic Framework for Dynamic Capacitated Arc Routing Problems.
IEEE Trans. Evol. Comput., 2022

Multitask Shape Optimization Using a 3-D Point Cloud Autoencoder as Unified Representation.
IEEE Trans. Evol. Comput., 2022

Dynamic Optimization in Fast-Changing Environments via Offline Evolutionary Search.
IEEE Trans. Evol. Comput., 2022

An Efficient Contesting Procedure for AutoML Optimization.
IEEE Access, 2022

A Systematic Approach to Analyze the Computational Cost of Robustness in Model-Assisted Robust Optimization.
Proceedings of the Parallel Problem Solving from Nature - PPSN XVII, 2022

Split-AE: An Autoencoder-based Disentanglement Framework for 3D Shape-to-shape Feature Transfer.
Proceedings of the International Joint Conference on Neural Networks, 2022

Spatio-Temporal Activity Recognition for Evolutionary Search Behavior Prediction.
Proceedings of the International Joint Conference on Neural Networks, 2022

What makes the dynamic capacitated Arc routing problem hard to solve: insights from fitness landscape analysis.
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022

Benchmarking Dynamic Capacitated Arc Routing Algorithms Using Real-World Traffic Simulation.
Proceedings of the IEEE Congress on Evolutionary Computation, 2022

Cooperative Multi-objective Topology Optimization Using Clustering and Metamodeling.
Proceedings of the IEEE Congress on Evolutionary Computation, 2022

2021
A Novel Generalised Meta-Heuristic Framework for Dynamic Capacitated Arc Routing Problems.
CoRR, 2021

Exploiting Generative Models for Performance Predictions of 3D Car Designs.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Efficient AutoML via Combinational Sampling.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Predicting CMA-ES Operators as Inductive Biases for Shape Optimization Problems.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Voxel-Based Three-Dimensional Neural Style Transfer.
Proceedings of the Advances in Computational Intelligence, 2021

Artificial Neural Networks as Feature Extractors in Continuous Evolutionary Optimization.
Proceedings of the International Joint Conference on Neural Networks, 2021

A new acquisition function for robust Bayesian optimization of unconstrained problems.
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

A hybrid local search framework for the dynamic capacitated arc routing problem.
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

Improved Automated CASH Optimization with Tree Parzen Estimators for Class Imbalance Problems.
Proceedings of the 8th IEEE International Conference on Data Science and Advanced Analytics, 2021

Exploiting Linear Interpolation of Variational Autoencoders for Satisfying Preferences in Evolutionary Design Optimization.
Proceedings of the IEEE Congress on Evolutionary Computation, 2021

Exploiting Local Geometric Features in Vehicle Design Optimization with 3D Point Cloud Autoencoders.
Proceedings of the IEEE Congress on Evolutionary Computation, 2021

Point2FFD: Learning Shape Representations of Simulation-Ready 3D Models for Engineering Design Optimization.
Proceedings of the International Conference on 3D Vision, 2021

2020
Exploring Clinical Time Series Forecasting with Meta-Features in Variational Recurrent Models.
Dataset, May, 2020

Computational Study on Effectiveness of Knowledge Transfer in Dynamic Multi-objective Optimization.
Dataset, May, 2020

On the Performance of Oversampling Techniques for Class Imbalance Problems.
Dataset, May, 2020

An Empirical Comparison of Meta-Modeling Techniques for Robust Design Optimization.
Dataset, February, 2020

When and How to Transfer Knowledge in Dynamic Multi-objective Optimization.
Dataset, February, 2020

Hyperparameter Optimisation for Improving Classification under Class Imbalance.
Dataset, February, 2020

Generating and Adapting to Diverse Ad-Hoc Cooperation Agents in Hanabi.
CoRR, 2020

Evaluating the Rainbow DQN Agent in Hanabi with Unseen Partners.
CoRR, 2020

A Compact Patch-Based Representation for Technical Mesh Models.
Proceedings of the 25th International Symposium on Vision, Modeling and Visualization, 2020

Exploring Dimensionality Reduction Techniques for Efficient Surrogate-Assisted optimization.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

Quantifying The Generative Capabilities Of Variational Autoencoders For 3D Car Point Clouds.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

Back To Meshes: Optimal Simulation-ready Mesh Prototypes For Autoencoder-based 3D Car Point Clouds.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

A Competitive Co-evolutionary optimization Method for the Dynamic Vehicle Routing Problem.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

An Effective Measure to Identify Meaningful Concepts in Engineering Design optimization.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

The Effects Of Non-linear Operators In Voxel-Based Deep Neural Networks For 3D Style Reconstruction.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

Towards Novel Meta-heuristic Algorithms for Dynamic Capacitated Arc Routing Problems.
Proceedings of the Parallel Problem Solving from Nature - PPSN XVI, 2020

Improving Imbalanced Classification by Anomaly Detection.
Proceedings of the Parallel Problem Solving from Nature - PPSN XVI, 2020

Improving Sampling in Evolution Strategies Through Mixture-Based Distributions Built from Past Problem Instances.
Proceedings of the Parallel Problem Solving from Nature - PPSN XVI, 2020

On the Performance of Oversampling Techniques for Class Imbalance Problems.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2020

Exploring Clinical Time Series Forecasting with Meta-Features in Variational Recurrent Models.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Feature Visualization for 3D Point Cloud Autoencoders.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Computational Study on Effectiveness of Knowledge Transfer in Dynamic Multi-objective Optimization.
Proceedings of the IEEE Congress on Evolutionary Computation, 2020

Representing Experience in Continuous Evolutionary optimisation through Problem-tailored Search Operators.
Proceedings of the IEEE Congress on Evolutionary Computation, 2020

Behavioral Evaluation of Hanabi Rainbow DQN Agents and Rule-Based Agents.
Proceedings of the Sixteenth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 2020

2019
Solving Incremental Optimization Problems via Cooperative Coevolution.
IEEE Trans. Evol. Comput., 2019

Competitive Co-evolution for Dynamic Constrained Optimisation.
CoRR, 2019

An Empirical Comparison of Meta-Modeling Techniques for Robust Design Optimization.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019

Optimal Evolutionary Optimization Hyper-parameters to Mimic Human User Behavior.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019

When and How to Transfer Knowledge in Dynamic Multi-objective Optimization.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019

Scalability of Learning Tasks on 3D CAE Models Using Point Cloud Autoencoders.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019

On the Efficiency of a Point Cloud Autoencoder as a Geometric Representation for Shape Optimization.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019

Addressing Complex Engineering Systems: The Value Of Evolvability.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019

Hyperparameter Optimisation for Improving Classification under Class Imbalance.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019

Learning Transferable Variation Operators in a Continuous Genetic Algorithm.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019

Standardization of Gram Matrix for Improved 3D Neural Style Transfer.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019

Learning Time-Series Data of Industrial Design Optimization using Recurrent Neural Networks.
Proceedings of the 2019 International Conference on Data Mining Workshops, 2019

Identifying Topological Prototypes using Deep Point Cloud Autoencoder Networks.
Proceedings of the 2019 International Conference on Data Mining Workshops, 2019

Diverse Agents for Ad-Hoc Cooperation in Hanabi.
Proceedings of the IEEE Conference on Games, 2019

2018
Cooperative Co-Evolution-Based Design Optimization: A Concurrent Engineering Perspective.
IEEE Trans. Evol. Comput., 2018

Orthogonalization of linear representations for efficient evolutionary design optimization.
Proceedings of the Genetic and Evolutionary Computation Conference, 2018

Evolving Agents for the Hanabi 2018 CIG Competition.
Proceedings of the 2018 IEEE Conference on Computational Intelligence and Games, 2018

Towards Game-based Metrics for Computational Co-Creativity.
Proceedings of the 2018 IEEE Conference on Computational Intelligence and Games, 2018

2017
Multi-objective Representation Setups for Deformation-Based Design Optimization.
Proceedings of the Evolutionary Multi-Criterion Optimization, 2017

Preference-guided adaptation of deformation representations for evolutionary design optimization.
Proceedings of the 2017 IEEE Congress on Evolutionary Computation, 2017

2016
Constrained space deformation techniques for design optimization.
Comput. Aided Des., 2016

Evolvability as a quality criterion for linear deformation representations in evolutionary optimization.
Proceedings of the IEEE Congress on Evolutionary Computation, 2016

2015
Evolvability of representations in complex system engineering: A survey.
Proceedings of the IEEE Congress on Evolutionary Computation, 2015

Kamera-Hardware.
Proceedings of the Handbuch Fahrerassistenzsysteme, 2015

2014
RBF morphing techniques for simulation-based design optimization.
Eng. Comput., 2014

The Performance Effects of Interaction Frequency in Parallel Cooperative Coevolution.
Proceedings of the Simulated Evolution and Learning - 10th International Conference, 2014

A cascaded evolutionary multi-objective optimization for solving the unbiased universal electric motor family problem.
Proceedings of the IEEE Congress on Evolutionary Computation, 2014

2013
Evolution by Adapting Surrogates.
Evol. Comput., 2013

2012
High Quality Mesh Morphing Using Triharmonic Radial Basis Functions.
Proceedings of the 21st International Meshing Roundtable, 2012

Decomposition of Multimodal Data for Affordance-based Identification of Potential Grasps.
Proceedings of the ICPRAM 2012, 2012

Application of Sensitivity Analysis for an Improved Representation in Evolutionary Design Optimization.
Proceedings of the 2012 Sixth International Conference on Genetic and Evolutionary Computing, 2012

Evolvability as concept for the optimal design of free-form deformation control volumes.
Proceedings of the IEEE Congress on Evolutionary Computation, 2012

Multi co-objective evolutionary optimization: Cross surrogate augmentation for computationally expensive problems.
Proceedings of the IEEE Congress on Evolutionary Computation, 2012

2011
Evolvable free-form deformation control volumes for evolutionary design optimization.
Proceedings of the IEEE Congress on Evolutionary Computation, 2011

2010
Correlating Shape and Functional Properties Using Decomposition Approaches.
Proceedings of the Twenty-Third International Florida Artificial Intelligence Research Society Conference, 2010

Finding correlations in multimodal data using decomposition approaches.
Proceedings of the 18th European Symposium on Artificial Neural Networks, 2010

2008
Representing the Change - Free Form Deformation for Evolutionary Design Optimization.
Proceedings of the Evolutionary Computation in Practice, 2008

Knowledge Extraction from Aerodynamic Design Data and its Application to 3D Turbine Blade Geometries.
J. Math. Model. Algorithms, 2008

Unsupervised extraction of design components for a 3D parts-based representation.
Proceedings of the International Joint Conference on Neural Networks, 2008

2007
Word Recognition with a Hierarchical Neural Network.
Proceedings of the Advances in Nonlinear Speech Processing, 2007

2006
Direct Manipulation of Free Form Deformation in Evolutionary Design Optimisation.
Proceedings of the Parallel Problem Solving from Nature, 2006


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