Asymmetric Heterogeneous Transfer Learning: A Survey. - Magda Friedjungová; Marcel Jirina (DATA, 2017)

An Overview of Transfer Learning Focused on Asymmetric Heterogeneous Approaches. - Magda Friedjungová; Marcel Jirina (DATA (Revised Selected Papers), 2017)

Constructing a Data Visualization Recommender System. - Petra Kubernátová; Magda Friedjungová; Max J. van Duijn (DATA (Revised Selected Papers), 2018)

Knowledge at First Glance: A Model for a Data Visualization Recommender System Suited for Non-expert Users. - Petra Kubernátová; Magda Friedjungová; Max J. van Duijn (DATA, 2018)

Missing Features Reconstruction and Its Impact on Classification Accuracy. - Magda Friedjungová; Marcel Jirina; Daniel Vasata (ICCS (3), 2019)

Unsupervised Latent Space Translation Network. - Magda Friedjungová; Daniel Vasata; Tomás Chobola; Marcel Jirina (ESANN, 2020)

Missing Features Reconstruction Using a Wasserstein Generative Adversarial Imputation Network. - Magda Friedjungová; Daniel Vasata; Maksym Balatsko; Marcel Jirina (ICCS (4), 2020)

Dynamic Neural Diversification: Path to Computationally Sustainable Neural Networks. - Alexander Kovalenko; Pavel Kordík; Magda Friedjungová (ICANN (2), 2021)

Image Inpainting Using Wasserstein Generative Adversarial Imputation Network. - Daniel Vasata; Tomás Halama; Magda Friedjungová (ICANN (2), 2021)

Road Quality Classification. - Martin Lank; Magda Friedjungová (ICIAP (2), 2022)

Towards Using Machine Learning to Generatively Simulate EV Charging in Urban Areas. - Marek Miltner; Jakub Zíka; Daniel Vasata; Artem Bryksa; Magda Friedjungová; Ondrej Stogl; Ram Rajagopal; Oldrich Starý (CoRR, 2024)