Neural Networks as Surrogate Models for Measurements in Optimization Algorithms. - Martin Holena; David Linke; Uwe Rodemerck; Lukás Bajer (ASMTA, 2010)

Surrogate Model for Continuous and Discrete Genetic Optimization Based on RBF Networks. - Lukás Bajer; Martin Holena (IDEAL, 2010)

Case study: constraint handling in evolutionary optimization of catalytic materials. - Martin Holena; David Linke; Lukás Bajer (GECCO (Companion), 2011)

Surrogate modeling in the evolutionary optimization of catalytic materials. - Martin Holena; David Linke; Lukás Bajer (GECCO, 2012)

RBF-based surrogate model for evolutionary optimization. - Lukás Bajer; Martin Holena (ITAT, 2012)

Model guided sampling optimization with gaussian processes for expensive black-box optimization. - Lukás Bajer; Viktor Charypar; Martin Holena (GECCO (Companion), 2013)

Surrogate Model for Mixed-Variables Evolutionary Optimization Based on GLM and RBF Networks. - Lukás Bajer; Martin Holena (SOFSEM, 2013)

Two Gaussian Approaches to Black-Box Optomization. - Lukás Bajer; Martin Holena (CoRR, 2014)

Benchmarking Gaussian Processes and Random Forests Surrogate Models on the BBOB Noiseless Testbed. - Lukás Bajer; Zbynek Pitra; Martin Holena (GECCO (Companion), 2015)

Investigation of Gaussian Processes and Random Forests as Surrogate Models for Evolutionary Black-Box Optimization. - Lukás Bajer; Zbynek Pitra; Martin Holena (GECCO (Companion), 2015)

Model Guided Sampling Optimization for Low-dimensional Problems. - Lukás Bajer; Martin Holena (ICAART (2), 2015)

Investigation of Gaussian Processes in the Context of Black-Box Evolutionary Optimization. - Andrej Kudinov; Lukás Bajer; Zbynek Pitra; Martin Holena (ITAT, 2015)

Comparing SVM, Gaussian Process and Random Forest Surrogate Models for the CMA-ES. - Zbynek Pitra; Lukás Bajer; Martin Holena (ITAT, 2015)

Using Copulas in Data Mining Based on the Observational Calculus. - Martin Holena; Lukás Bajer; Martin Scavnicky (IEEE Trans. Knowl. Data Eng., 2015)

Testing Gaussian Process Surrogates on CEC'2013 Multi-Modal Benchmark. - Nikita Orekhov; Lukás Bajer; Martin Holena (ITAT, 2016)

Traditional Gaussian Process Surrogates in the BBOB Framework. - Jakub Repický; Lukás Bajer; Martin Holena (ITAT, 2016)

Doubly Trained Evolution Control for the Surrogate CMA-ES. - Zbynek Pitra; Lukás Bajer; Martin Holena (PPSN, 2016)

Ordinal versus metric gaussian process regression in surrogate modelling for CMA evolution strategy. - Zbynek Pitra; Lukás Bajer; Jakub Repický; Martin Holena (GECCO (Companion), 2017)

Overview of surrogate-model versions of covariance matrix adaptation evolution strategy. - Zbynek Pitra; Lukás Bajer; Jakub Repický; Martin Holena (GECCO (Companion), 2017)

Comparison of ordinal and metric gaussian process regression as surrogate models for CMA evolution strategy. - Zbynek Pitra; Lukás Bajer; Jakub Repický; Martin Holena (GECCO (Companion), 2017)

Adaptive Doubly Trained Evolution Control for the Covariance Matrix Adaptation Evolution Strategy. - Zbynek Pitra; Lukás Bajer; Jakub Repický; Martin Holena (ITAT, 2017)

Adaptive Generation-Based Evolution Control for Gaussian Process Surrogate Models. - Jakub Repický; Lukás Bajer; Zbynek Pitra; Martin Holena (ITAT, 2017)

Gaussian process surrogate models for the CMA-ES. - Lukás Bajer; Zbynek Pitra; Jakub Repický; Martin Holena (GECCO (Companion), 2019)

Gaussian Process Surrogate Models for the CMA Evolution Strategy. - Lukás Bajer; Zbynek Pitra; Jakub Repický; Martin Holena (Evol. Comput., 2019)

Loss Functions for Clustering in Multi-instance Learning. - Marek Dedic; Tomás Pevný; Lukás Bajer; Martin Holena (ITAT, 2020)

Learning Explainable Representations of Malware Behavior. - Paul Prasse; Jan Brabec; Jan Kohout; Martin Kopp; Lukás Bajer; Tobias Scheffer (ECML/PKDD (4), 2021)

GNN-Based Malicious Network Entities Identification In Large-Scale Network Data. - Stepan Dvorak; Pavel Procházka; Lukás Bajer (NOMS, 2022)

Balancing performance and complexity with adaptive graph coarsening. - Marek Dedic; Lukás Bajer; Pavel Procházka; Martin Holena (Tiny Papers @ ICLR, 2024)

Convolutional Signal Propagation: A Simple Scalable Algorithm for Hypergraphs. - Pavel Procházka; Marek Dedic; Lukás Bajer (CoRR, 2024)

Malicious Internet Entity Detection Using Local Graph Inference. - Simon Mandlík; Tomás Pevný; Václav Smídl; Lukás Bajer (IEEE Trans. Inf. Forensics Secur., 2024)