- Feature Extraction for Surrogate Models in Genetic Programming2016 | Faculty of Mathematics and Physics
- The Selection of Surrogate Models in Evolutionary Algorithms2012 | Faculty of Mathematics and Physics
- Hypervolume-Based Surrogate Model for MO-CMA-ES2015 | Faculty of Mathematics and Physics
- RBF-based surrogate model for evolutionary optimization2012 | Faculty of Mathematics and Physics
- Using graph neural networks as surrogate models in genetic programming2022 | Faculty of Mathematics and Physics
- Surrogate Model for Continuous and Discrete Genetic Optimization Based on RBF Networks2010 | Faculty of Mathematics and Physics
- ASM-MOMA: Multiobjective Memetic Algorithm with Aggregate Surrogate Model2011 | Faculty of Mathematics and Physics
- Benchmarking Gaussian Processes and Random Forests Surrogate Models on the BBOB Noiseless Testbed2015 | Faculty of Mathematics and Physics
- Investigation of Gaussian Processes and Random Forests As Surrogate Models for Evolutionary Black-Box Optimization2015 | Faculty of Mathematics and Physics
- Surrogate Model for Mixed-Variables Evolutionary Optimization Based on GLM and RBF Networks2013 | Faculty of Mathematics and Physics
- Combining Gaussian processes and neural networks in surrogate modeling for covariance matrix adaptation evolution strategy2021 | Faculty of Mathematics and Physics, Central Library of Charles University
- Multi-objectivization and Surrogate Modelling for Neural Network Hyper-parameters Tuning2013 | Faculty of Mathematics and Physics
- Surrogate Model Selection for Evolutionary Multiobjective Optimization2013 | Faculty of Mathematics and Physics
- An Evolutionary Strategy for Surrogate-Based Multiobjective Optimization2012 | Faculty of Mathematics and Physics
- Traditional Gaussian Process Surrogates in the BBOB Framework2016 | Faculty of Mathematics and Physics
- Testing Gaussian Process Surrogates on CEC'2013 multi-modal benchmark2016 | Faculty of Mathematics and Physics
- Towards Surrogate Assisted Estimation of Distribution Algorithms2012 | Faculty of Mathematics and Physics
- Doubly Trained Evolution Control for the Surrogate CMA-ES2016 | Faculty of Mathematics and Physics
- Meta-Learning and Model Selection in Multiobjective Evolutionary Algorithms2012 | Faculty of Mathematics and Physics
- Interaction between Model and Its Evolution Control in Surrogate-Assisted CMA Evolution Strategy2021 | Faculty of Mathematics and Physics, Central Library of Charles University
- The effect of different local search algorithms on the performance of multi-objective optimizers2014 | Faculty of Mathematics and Physics
- Towards Low-dimensional Gaussian Process Metamodels for CMA-ES2014 | Faculty of Mathematics and Physics
- LAMM-MMA: Multiobjective Memetic Algorithm with Local Aggregate Meta-Model2011 | Faculty of Mathematics and Physics
- Local Meta-models for ASM-MOMA2011 | Faculty of Mathematics and Physics
- Multiobjective Memetic Algorithm with Local Meta-Models2011 | Faculty of Mathematics and Physics
- Hypervolume-based local search in multi-objective evolutionary optimization2014 | Faculty of Mathematics and Physics
- Neural-network-based estimation of normal distributions in black-box optimization2022 | Faculty of Mathematics and Physics
- Aggregate meta-models for evolutionary multiobjective and many-objective optimization2013 | Faculty of Mathematics and Physics
- Combining Parameter Space Search and Meta-learning for Data-Dependent Computational Agent Recommendation2012 | Faculty of Mathematics and Physics
- Combining Gaussian Processes with Neural Networks for Active Learning in OptimizationPublication without faculty affiliation