Two Semi-supervised Approaches to Malware Detection with Neural Networks. - Jan Koza; Marek Krcál; Martin Holena (ITAT, 2020)

Interaction between model and its evolution control in surrogate-assisted CMA evolution strategy. - Zbynek Pitra; Marek Hanus; Jan Koza; Jirí Tumpach; Martin Holena (GECCO, 2021)

Combining Gaussian Processes and Neural Networks in Surrogate Modelling for Covariance Matrix Adaptation Evolution Strategy. - Jan Koza; Jirí Tumpach; Zbynek Pitra; Martin Holena (ITAT, 2021)

Using Past Experience for Configuration of Gaussian Processes in Black-Box Optimization. - Jan Koza; Jirí Tumpach; Zbynek Pitra; Martin Holena (LION, 2021)

Combining Gaussian Processes with Neural Networks for Active Learning in Optimization. - Jirí Ruzicka; Jan Koza; Jirí Tumpach; Zbynek Pitra; Martin Holena (IAL@PKDD/ECML, 2021)

Neural-network-based estimation of normal distributions in black-box optimization. - Jirí Tumpach; Jan Koza; Martin Holena (ESANN, 2022)

Improving Optimization with Gaussian Processes in the Covariance Matrix Adaptation Evolution Strategy. - Jirí Tumpach; Jan Koza; Martin Holena (ITAT, 2023)

Suitability of Modern Neural Networks for Active and Transfer Learning in Surrogate-Assisted Black-Box Optimization. - Martin Holena; Jan Koza (IAL@PKDD/ECML, 2024)

Landscape Analysis for Surrogate Models in the Evolutionary Black-Box Context. - Zbynek Pitra; Jan Koza; Jirí Tumpach; Martin Holena (Evol. Comput., 2025)