Mirrored orthogonal sampling with pairwise selection in evolution strategies. - Hao Wang 025; Michael Emmerich 001; Thomas Bäck (SAC, 2014)

Multi-point Efficient Global Optimization Using Niching Evolution Strategy. - Hao Wang 025; Thomas Bäck; Michael T. M. Emmerich (EVOLVE, 2015)

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

On Steering Dominated Points in Hypervolume Indicator Gradient Ascent for Bi-Objective Optimization. - Hao Wang 025; Yiyi Ren; André H. Deutz; Michael T. M. Emmerich (NEO, 2015)

A Multicriteria Generalization of Bayesian Global Optimization. - Michael Emmerich 001; Kaifeng Yang; André H. Deutz; Hao Wang 025; Carlos M. Fonseca (Advances in Stochastic and Deterministic Global Optimization, 2016)

Balancing risk and expected gain in kriging-based global optimization. - Hao Wang 025; Michael T. M. Emmerich; Thomas Bäck (CEC, 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)

SMS-EMOA with multiple dynamic reference points. - Zhiwei Yang 002; Hao Wang 025; Kaifeng Yang; Thomas Bäck; Michael Emmerich 001 (ICNC-FSKD, 2016)

Towards Analyzing Multimodality of Continuous Multiobjective Landscapes. - Pascal Kerschke; Hao Wang 025; Mike Preuss; Christian Grimme; André H. Deutz; Heike Trautmann; Michael Emmerich 001 (PPSN, 2016)

Evolving the structure of Evolution Strategies. - Sander van Rijn; Hao Wang 025; Matthijs van Leeuwen; Thomas Bäck (SSCI, 2016)

Hypervolume Indicator Gradient Ascent Multi-objective Optimization. - Hao Wang 025; André H. Deutz; Thomas Bäck; Michael Emmerich 001 (EMO, 2017)

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)

Boosting Quantum Annealing Performance Using Evolution Strategies for Annealing Offsets Tuning. - Sheir Yarkoni; Hao Wang 025; Aske Plaat; Thomas Bäck (QTOP@NetSys, 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)

Cooling Strategies for the Moment-Generating Function in Bayesian Global Optimization. - Hao Wang 025; Michael Emmerich 001; Thomas Bäck (CEC, 2018)

Ranking empirical cumulative distribution functions using stochastic and pareto dominance. - Hao Wang 025; Thomas Bäck (GECCO (Companion), 2018)

Towards a theory-guided benchmarking suite for discrete black-box optimization heuristics: profiling (1 + λ) EA variants on onemax and leadingones. - Carola Doerr; Furong Ye; Sander van Rijn; Hao Wang 025; Thomas Bäck (GECCO, 2018)

Machine Learning for Predicting the Damaged Parts of a Low Speed Vehicle Crash. - Milan Koch; Hao Wang 025; Thomas Bäck (ICDIM, 2018)

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

IOHprofiler: A Benchmarking and Profiling Tool for Iterative Optimization Heuristics. - Carola Doerr; Hao Wang 025; Furong Ye; Sander van Rijn; Thomas Bäck (CoRR, 2018)

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

Evolution Strategies. - Michael Emmerich 001; Ofer M. Shir; Hao Wang 025 (Handbook of Heuristics, 2018)

Automated Machine Learning for EEG-Based Classification of Parkinson's Disease Patients. - Milan Koch; Victor Geraedts; Hao Wang 025; Martijn Tannemaat; Thomas Bäck (IEEE BigData, 2019)

Hyper-Parameter Optimization for Improving the Performance of Grammatical Evolution. - Hao Wang 025; Yitan Lou; Thomas Bäck (CEC, 2019)

On the potential of evolution strategies for neural network weight optimization. - Hao Wang 025; Thomas Bäck; Aske Plaat; Michael Emmerich 001; Mike Preuss (GECCO (Companion), 2019)

Bayesian performance analysis for black-box optimization benchmarking. - Borja Calvo; Ofer M. Shir; Josu Ceberio; Carola Doerr; Hao Wang 025; Thomas Bäck; José Antonio Lozano 001 (GECCO (Companion), 2019)

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

Anomaly Detection in Univariate Time Series: An Empirical Comparison of Machine Learning Algorithms. - Sina Däubener; Sebastian Schmitt; Hao Wang 025; Peter Krause 001; Thomas Bäck (ICDM, 2019)

Switching Between Swarm Optimization Algorithms During a Run: An Empirical Study. - Teddy Etoeharnowo; Koen Castelein; Hao Wang 025; Thomas Bäck (SSCI, 2019)

An Empirical Comparison of Meta-Modeling Techniques for Robust Design Optimization. - Sibghat Ullah; Hao Wang 025; Stefan Menzel; Bernhard Sendhoff; Thomas Bäck (SSCI, 2019)

Sequential vs. Integrated Algorithm Selection and Configuration: A Case Study for the Modular CMA-ES. - Diederick Vermetten; Hao Wang 025; Carola Doerr; Thomas Bäck (CoRR, 2019)

Search Dynamics on Multimodal Multiobjective Problems. - Pascal Kerschke; Hao Wang 025; Mike Preuss; Christian Grimme; André H. Deutz; Heike Trautmann; Michael T. M. Emmerich (Evol. Comput., 2019)

Mirrored Orthogonal Sampling for Covariance Matrix Adaptation Evolution Strategies. - Hao Wang 025; Michael Emmerich 001; Thomas Bäck (Evol. Comput., 2019)

Automated Machine Learning for the Classification of Normal and Abnormal Electromyography Data. - Marios Kefalas; Milan Koch; Victor Geraedts; Hao Wang 025; Martijn Tannemaat; Thomas Bäck (IEEE BigData, 2020)

Can Single Solution Optimisation Methods Be Structurally Biased? - Anna V. Kononova; Fabio Caraffini; Hao Wang 025; Thomas Bäck (CEC, 2020)

A modular hybridization of particle swarm optimization and differential evolution. - Rick Boks; Hao Wang 025; Thomas Bäck (GECCO Companion, 2020)

Towards dynamic algorithm selection for numerical black-box optimization: investigating BBOB as a use case. - Diederick Vermetten; Hao Wang 025; Thomas Bäck; Carola Doerr (GECCO, 2020)

Integrated vs. sequential approaches for selecting and tuning CMA-ES variants. - Diederick Vermetten; Hao Wang 025; Carola Doerr; Thomas Bäck (GECCO, 2020)

Benchmarking and analyzing iterative optimization heuristics with IOHprofiler. - Hao Wang 025; Carola Doerr; Ofer M. Shir; Thomas Bäck (GECCO Companion, 2020)

Exploring Clinical Time Series Forecasting with Meta-Features in Variational Recurrent Models. - Ullah Ullah; Zhao Xu 001; Hao Wang 025; Stefan Menzel; Bernhard Sendhoff; Thomas Bäck (IJCNN, 2020)

A Classification-based Solution For Recommending Process Parameters of Production Processes Without Quality Measures. - Zhengtian Ai; Ingo Heinle; Christian Schelske; Hao Wang 025; Peter Krause 001; Thomas Bäck (ISM, 2020)

Can Compact Optimisation Algorithms Be Structurally Biased? - Anna V. Kononova; Fabio Caraffini; Hao Wang 025; Thomas Bäck (PPSN (1), 2020)

High Dimensional Bayesian Optimization Assisted by Principal Component Analysis. - Elena Raponi; Hao Wang 025; Mariusz Bujny; Simonetta Boria; Carola Doerr (PPSN (1), 2020)

Benchmarking a (μ +λ ) Genetic Algorithm with Configurable Crossover Probability. - Furong Ye; Hao Wang 025; Carola Doerr; Thomas Bäck (PPSN (2), 2020)

Per-Instance Configuration of the Modularized CMA-ES by Means of Classifier Chains and Exploratory Landscape Analysis. - Raphael Patrick Prager; Heike Trautmann; Hao Wang 025; Thomas Bäck; Pascal Kerschke (SSCI, 2020)

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

Exploring Dimensionality Reduction Techniques for Efficient Surrogate-Assisted optimization. - Sibghat Ullah; Duc Anh Nguyen; Hao Wang 025; Stefan Menzel; Bernhard Sendhoff; Thomas Bäck (SSCI, 2020)

Towards Data-driven Services in Vehicles. - Milan Koch; Hao Wang 025; Robert Bürgel; Thomas Bäck (VEHITS, 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)

Benchmarking discrete optimization heuristics with IOHprofiler. - Carola Doerr; Furong Ye; Naama Horesh; Hao Wang 025; Ofer M. Shir; Thomas Bäck (Appl. Soft Comput., 2020)

IOHanalyzer: Performance Analysis for Iterative Optimization Heuristic. - Hao Wang 025; Diederick Vermetten; Furong Ye; Carola Doerr; Thomas Bäck (CoRR, 2020)

Squirrel: A Switching Hyperparameter Optimizer. - Noor H. Awad; Gresa Shala; Difan Deng; Neeratyoy Mallik; Matthias Feurer; Katharina Eggensperger; André Biedenkapp; Diederick Vermetten; Hao Wang 025; Carola Doerr; Marius Lindauer; Frank Hutter (CoRR, 2020)

The Set-Based Hypervolume Newton Method for Bi-Objective Optimization. - Víctor Adrián Sosa-Hernández; Oliver Schütze 001; Hao Wang 025; André H. Deutz; Michael Emmerich 001 (IEEE Trans. Cybern., 2020)

An Empirical Comparison of Meta-Modeling Techniques for Robust Design Optimization. - Sibghat Ullah; Hao Wang 025; Stefan Menzel; Thomas Bäck; Bernhard Sendhoff (Zenodo, 2020)

The Experimental Data Sets for the study "Benchmarking a (μ+λ) Genetic Algorithm withConfigurable Crossover Probability". - Furong Ye; Hao Wang 025; Carola Doerr; Thomas Bäck (Zenodo, 2020)

Experimental Data Sets for the study "Benchmarking a (μ+λ) Genetic Algorithm with Configurable Crossover Probability". - Furong Ye; Hao Wang 025; Carola Doerr; Thomas Bäck (Zenodo, 2020)

Experimental Data Sets for the study "Benchmarking a (μ+λ) Genetic Algorithm with Configurable Crossover Probability". - Furong Ye; Hao Wang 025; Carola Doerr; Thomas Bäck (Zenodo, 2020)

Experimental Results for the study "A Modular Hybridization of Particle Swarm Optimization and Differential Evolution". - Rick Boks; Hao Wang 025; Thomas Bäck (Zenodo, 2020)

Exploring Clinical Time Series Forecasting with Meta-Features in Variational Recurrent Models. - Sibghat Ullah; Zhao Xu 001; Hao Wang 025; Stefan Menzel; Bernhard Sendhoff (Zenodo, 2020)

Improved Automated CASH Optimization with Tree Parzen Estimators for Class Imbalance Problems. - Duc Anh Nguyen; Jiawen Kong; Hao Wang 025; Stefan Menzel; Bernhard Sendhoff; Anna V. Kononova; Thomas Bäck (DSAA, 2021)

On Statistical Analysis of MOEAs with Multiple Performance Indicators. - Hao Wang 025; Carlos Ignacio Hernández Castellanos; Tome Eftimov (EMO, 2021)

Tabu-Driven Quantum Neighborhood Samplers. - Charles Moussa; Hao Wang 025; Henri Calandra; Thomas Bäck; Vedran Dunjko (EvoCOP, 2021)

Quantifying the impact of boundary constraint handling methods on differential evolution. - Rick Boks; Anna V. Kononova; Hao Wang 025 (GECCO Companion, 2021)

Explorative data analysis of time series based algorithm features of CMA-ES variants. - Jacob de Nobel; Hao Wang 025; Thomas Bäck (GECCO, 2021)

Tuning as a means of assessing the benefits of new ideas in interplay with existing algorithmic modules. - Jacob de Nobel; Diederick Vermetten; Hao Wang 025; Carola Doerr; Thomas Bäck (GECCO Companion, 2021)

A new acquisition function for robust Bayesian optimization of unconstrained problems. - Sibghat Ullah; Hao Wang 025; Stefan Menzel; Bernhard Sendhoff; Thomas Bäck (GECCO Companion, 2021)

Is there anisotropy in structural bias? - Diederick Vermetten; Anna V. Kononova; Fabio Caraffini; Hao Wang 025; Thomas Bäck (GECCO Companion, 2021)

Bayesian neural architecture search using a training-free performance metric. - Andrés Camero; Hao Wang 025; Enrique Alba 001; Thomas Bäck (Appl. Soft Comput., 2021)

Temporal convolutional autoencoder for unsupervised anomaly detection in time series. - Markus Thill; Wolfgang Konen; Hao Wang 025; Thomas Bäck (Appl. Soft Comput., 2021)

Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization. - Christian Grimme; Pascal Kerschke; Pelin Aspar; Heike Trautmann; Mike Preuss; André H. Deutz; Hao Wang 025; Michael Emmerich 001 (Comput. Oper. Res., 2021)

Explorative Data Analysis of Time Series based AlgorithmFeatures of CMA-ES Variants. - Jacob de Nobel; Hao Wang 025; Thomas Bäck (CoRR, 2021)

Data sets for the study "Automated Configuration of Genetic Algorithms by Tuning for Anytime Performance.". - Furong Ye; Carola Doerr; Hao Wang 025; Thomas Bäck (Zenodo, 2021)

IOHanalyzer version 0.1.6.1 + example datasets. - Diederick Vermetten; Hao Wang 025; Furong Ye; Carola Doerr; Thomas Bäck (Zenodo, 2021)

Benchmarking and analyzing iterative optimization heuristics with IOH profiler. - Carola Doerr; Hao Wang 025; Diederick Vermetten; Thomas Bäck; Jacob de Nobel; Furong Ye (GECCO Companion, 2022)

Analyzing the impact of undersampling on the benchmarking and configuration of evolutionary algorithms. - Diederick Vermetten; Hao Wang 025; Manuel López-Ibáñez 001; Carola Doerr; Thomas Bäck (GECCO, 2022)

IOHanalyzer: Detailed performance analyses for iterative optimization heuristics: hot-off-the-press track @ GECCO 2022. - Hao Wang 025; Diederick Vermetten; Furong Ye; Carola Doerr; Thomas Bäck (GECCO Companion, 2022)

Automated configuration of genetic algorithms by tuning for anytime performance: hot-off-the-press track at GECCCO 2022. - Furong Ye; Carola Doerr; Hao Wang 025; Thomas Bäck (GECCO Companion, 2022)

High Dimensional Bayesian Optimization with Kernel Principal Component Analysis. - Kirill A. Antonov; Elena Raponi; Hao Wang 025; Carola Doerr (PPSN (1), 2022)

Per-run Algorithm Selection with Warm-Starting Using Trajectory-Based Features. - Ana Kostovska; Anja Jankovic 001; Diederick Vermetten; Jacob de Nobel; Hao Wang 025; Tome Eftimov; Carola Doerr (PPSN (1), 2022)

A Systematic Approach to Analyze the Computational Cost of Robustness in Model-Assisted Robust Optimization. - Sibghat Ullah; Hao Wang 025; Stefan Menzel; Bernhard Sendhoff; Thomas Bäck (PPSN (1), 2022)

Chaining of Numerical Black-box Algorithms: Warm-Starting and Switching Points. - Dominik Schröder; Diederick Vermetten; Hao Wang 025; Carola Doerr; Thomas Bäck (CoRR, 2022)

Probability Distribution of Hypervolume Improvement in Bi-objective Bayesian Optimization. - Hao Wang 025; Kaifeng Yang; Michael Affenzeller; Michael Emmerich 001 (CoRR, 2022)

Automated Configuration of Genetic Algorithms by Tuning for Anytime Performance. - Furong Ye; Carola Doerr; Hao Wang 025; Thomas Bäck (IEEE Trans. Evol. Comput., 2022)

IOHanalyzer: Detailed Performance Analyses for Iterative Optimization Heuristics. - Hao Wang 025; Diederick Vermetten; Furong Ye; Carola Doerr; Thomas Bäck (ACM Trans. Evol. Learn. Optim., 2022)

Analyzing the Impact of Undersampling on the Benchmarkingand Configuration of Evolutionary Algorithms - Dataset. - Diederick Vermetten; Hao Wang 025; Manuel López-Ibáñez 001; Carola Doerr; Thomas Bäck (Zenodo, 2022)

Per-Run Algorithm Selection with Warm-starting using Trajectory-based Features - Data. - Anja Jankovic 001; Ana Kostovska; Diederick Vermetten; Jacob de Nobel; Hao Wang 025; Tome Eftimov; Carola Doerr (Zenodo, 2022)

To Switch or not to Switch: Predicting the Benefit of Switching between Algorithms based on Trajectory Features - Dataset. - Diederick Vermetten; Hao Wang 025; Kevin Sim; Emma Hart (Zenodo, 2022)

Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler. - Frank Neumann 001; Aneta Neumann; Chao Qian 001; Anh Viet Do; Jacob de Nobel; Diederick Vermetten; Saba Sadeghi Ahouei; Furong Ye; Hao Wang 025; Thomas Bäck (CEC, 2023)

The Hypervolume Indicator Hessian Matrix: Analytical Expression, Computational Time Complexity, and Sparsity. - André H. Deutz; Michael Emmerich 001; Hao Wang 025 (EMO, 2023)

To Switch or Not to Switch: Predicting the Benefit of Switching Between Algorithms Based on Trajectory Features. - Diederick Vermetten; Hao Wang 025; Kevin Sim; Emma Hart (EvoApplications@EvoStar, 2023)

Benchmarking and analyzing iterative optimization heuristics with IOHprofiler. - Carola Doerr; Hao Wang 025; Diederick Vermetten; Thomas Bäck; Jacob de Nobel; Furong Ye (GECCO Companion, 2023)

Application of quantum-inspired generative models to small molecular datasets. - Charles Moussa; Hao Wang 025; Mauricio Araya-Polo; Thomas Bäck; Vedran Dunjko (QCE, 2023)

Benchmarking Adaptive Quantum Circuit Optimization Algorithms for Quantum Chemistry. - Waheeda Saib; Xavier Bonet-Monroig; Vedran Dunjko; Ivano Tavernelli; Thomas Bäck; Hao Wang 025 (QCE, 2023)

Adversarial Latent Autoencoder with Self-Attention for Structural Image Synthesis. - Jiajie Fan; Laure Vuaille; Hao Wang 025; Thomas Bäck (CoRR, 2023)

On the Noise Scheduling for Generating Plausible Designs with Diffusion Models. - Jiajie Fan; Laure Vuaille; Thomas Bäck; Hao Wang 025 (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)

Bayesian Optimization. - Hao Wang 025; Kaifeng Yang (Many-Criteria Optimization and Decision Analysis, 2023)

Experimental Results for the study "The Hypervolume Newton Method for Constrained Multi-Objective Optimization Problems". - Hao Wang 025; Michael Emmerich 001; André H. Deutz; Víctor Adrián Sosa-Hernández; Oliver Schütze 001 (Zenodo, 2023)

Classification-based process parameter recommendation in sheet metal forming. - Zhengtian Ai; Ingo Heinle; Christian Schelske; Hao Wang 025; Peter Krause 001; Thomas Bäck (J. Ind. Inf. Integr., 2023)

Enhancing Plausibility Evaluation for Generated Designs with Denoising Autoencoder. - Jiajie Fan; Amal Trigui; Thomas Bäck; Hao Wang 025 (ECCV (78), 2024)

Transfer Learning of Surrogate Models via Domain Affine Transformation. - Shuaiqun Pan; Diederick Vermetten; Manuel López-Ibáñez 001; Thomas Bäck; Hao Wang 025 (GECCO, 2024)

Large-Scale Benchmarking of Metaphor-Based Optimization Heuristics. - Diederick Vermetten; Carola Doerr; Hao Wang 025; Anna V. Kononova; Thomas Bäck (GECCO, 2024)

Probability Distribution of Hypervolume Improvement in Bi-objective Bayesian Optimization. - Hao Wang 025; Kaifeng Yang; Michael Affenzeller (ICML, 2024)

Optical next generation reservoir computing. - Hao Wang 025; Jianqi Hu; YoonSeok Baek; Kohei Tsuchiyama; Malo Joly; Qiang Liu; Sylvain Gigan (CoRR, 2024)

A Newton Method for Hausdorff Approximations of the Pareto Front within Multi-objective Evolutionary Algorithms. - Hao Wang 025; Angel E. Rodriguez-Fernandez; Lourdes Uribe; André H. Deutz; Oziel Cortés-Piña; Oliver Schütze 001 (CoRR, 2024)

NeuroNURBS: Learning Efficient Surface Representations for 3D Solids. - Jiajie Fan; Babak Gholami; Thomas Bäck; Hao Wang 025 (CoRR, 2024)

IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics. - Jacob de Nobel; Furong Ye; Diederick Vermetten; Hao Wang 025; Carola Doerr; Thomas Bäck (Evol. Comput., 2024)

Large-Scale Benchmarking of Metaphor-Based Optimization Heuristics - Reproducibility Files. - Diederick Vermetten; Carola Doerr; Hao Wang 025; Anna V. Kononova; Thomas Bäck (Zenodo, 2024)

Large-scale photonic computing with nonlinear disordered media. - Hao Wang 025; Jianqi Hu; Andrea Morandi; Alfonso Nardi; Fei Xia; Xuanchen Li; Romolo Savo; Qiang Liu; Rachel Grange; Sylvain Gigan (Nat. Comput. Sci., 2024)

Transfer Learning of Surrogate Models via Domain Affine Transformation Across Synthetic and Real-World Benchmarks. - Shuaiqun Pan; Diederick Vermetten; Manuel López-Ibáñez 001; Thomas Bäck; Hao Wang 025 (CEC, 2025)

An Adaptive Re-evaluation Method for Evolution Strategy under Additive Noise. - Catalin-Viorel Dinu; Yash J. Patel; Xavier Bonet-Monroig; Hao Wang 025 (GECCO, 2025)

Abnormal Mutations: Evolution Strategies Don't Require Gaussianity. - Jacob de Nobel; Diederick Vermetten; Hao Wang 025; Anna V. Kononova; Günter Rudolph; Thomas Bäck (GECCO, 2025)

Evolving Hard Maximum Cut Instances for Quantum Approximate Optimization Algorithms. - Shuaiqun Pan; Yash J. Patel; Aneta Neumann; Frank Neumann 001; Thomas Bäck; Hao Wang 025 (GECCO, 2025)

Transfer Learning of Surrogate Models: Integrating Domain Warping and Affine Transformations. - Shuaiqun Pan; Diederick Vermetten; Manuel López-Ibáñez 001; Thomas Bäck; Hao Wang 025 (CoRR, 2025)

A Mesh Is Worth 512 Numbers: Spectral-domain Diffusion Modeling for High-dimension Shape Generation. - Jiajie Fan; Amal Trigui; Andrea Bonfanti; Felix Dietrich; Thomas Bäck; Hao Wang 025 (CoRR, 2025)

MMD-Newton Method for Multi-objective Optimization. - Hao Wang 025; Chenyu Shi; Angel E. Rodriguez-Fernandez; Oliver Schütze 001 (CoRR, 2025)