Deep Networks in Online Malware Detection. - Jirí Tumpach; Marek Krcál; Martin Holena (ITAT, 2019)

Online Malware Detection with Variational Autoencoders. - Jirí Tumpach; 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)

Video Scene Location Recognition with Neural Networks. - Lukás Korel; Petr Pulc; Jirí Tumpach; Martin Holena (ITAT, 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)

A Comparison of Regularization Techniques for Shallow Neural NetworksTrained on Small Datasets. - Jirí Tumpach; Jan Kalina; 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)

On Combining Robustness and Regularization in Training Multilayer Perceptrons over Small Data. - Jan Kalina; Jirí Tumpach; Martin Holena (IJCNN, 2022)

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

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