Learning Complex Bayesian Network Features for Classification. - Peter Antal; András Gézsi; Gábor Hullám; András Millinghoffer (Probabilistic Graphical Models, 2006)

A Bayesian View of Challenges in Feature Selection: Feature Aggregation, Multiple Targets, Redundancy and Interaction. - Peter Antal; András Millinghoffer; Gábor Hullám; Csaba Szalai; András Falus (FSDM, 2008)

Evaluation of a Bayesian model-based approach in GA studies. - Gábor Hullám; Peter Antal; Csaba Szalai; András Falus (MLSB, 2010)

Towards a Bayesian Decision Theoretic Analysis of Contextual Effect Modifiers. - Gábor Hullám; Peter Antal (Probabilistic Graphical Models, 2014)

Bayesian Relevance and Effect Size Measures - Gábor Hullám (2016)

Structural and parametric uncertainties in full Bayesian and graphical lasso based approaches: Beyond edge weights in psychological networks. - Gábor Hullám; Gabriella Juhász; Bill Deakin; Peter Antal (CIBCB, 2017)

Automatic lung segmentation in CT scans using guided filtering. - Gabor Revy; Daniel Hadhazi; Gábor Hullám (ICBRA, 2022)

Automatic Spine Segmentation in CT Scans. - Gabor Revy; Daniel Hadhazi; Gábor Hullám (BIOIMAGING, 2023)

Detection of Microcalcifications in Mammograms Using Algorithmic Filtering and Region-Based Neural Networks. - Daniel Hadhazi; Mihaly Vetro; Gábor Hullám (MeMeA, 2024)

Heart Segmentation on PA Chest X-Ray Images by Model-Based Deep Learning Approach. - Adam Tumay; Daniel Hadhazi; Gábor Hullám (MeMeA, 2024)