Mol-CycleGAN - A Generative Model for Molecular Optimization. - Lukasz Maziarka; Agnieszka Pocha; Jan Kaczmarczyk; Krzysztof Rataj; Michal Warchol (ICANN (Workshop), 2019)

The importance of standardisation - COVID-19 CT & Radiograph Image Data Stock for deep learning purpose. - Krzysztof Misztal; Agnieszka Pocha; Martyna Durak-Kozica; Michal Wator; Aleksandra Kubica-Misztal; Marcin Hartel (Comput. Biol. Medicine, 2020)

Comparison of Atom Representations in Graph Neural Networks for Molecular Property Prediction. - Agnieszka Pocha; Tomasz Danel; Lukasz Maziarka (CoRR, 2020)

Mol-CycleGAN: a generative model for molecular optimization. - Lukasz Maziarka; Agnieszka Pocha; Jan Kaczmarczyk; Krzysztof Rataj; Tomasz Danel; Michal Warchol (J. Cheminformatics, 2020)

Emulating Docking Results Using a Deep Neural Network: A New Perspective for Virtual Screening. - Stanislaw Jastrzebski; Maciej Szymczak; Agnieszka Pocha; Stefan Mordalski; Jacek Tabor; Andrzej J. Bojarski; Sabina Podlewska (J. Chem. Inf. Model., 2020)

Comparison of Atom Representations in Graph Neural Networks for Molecular Property Prediction. - Agnieszka Pocha; Tomasz Danel; Sabina Podlewska; Jacek Tabor; Lukasz Maziarka (IJCNN, 2021)

2D SIFt: a matrix of ligand-receptor interactions. - Stefan Mordalski; Agnieszka Wojtuch; Igor T. Podolak; Rafal Kurczab; Andrzej J. Bojarski (J. Cheminformatics, 2021)

How can SHAP values help to shape metabolic stability of chemical compounds? - Agnieszka Wojtuch; Rafal Jankowski; Sabina Podlewska (J. Cheminformatics, 2021)

Extended study on atomic featurization in graph neural networks for molecular property prediction. - Agnieszka Wojtuch; Tomasz Danel; Sabina Podlewska; Lukasz Maziarka (J. Cheminformatics, 2023)