Deep Dynamic Mixed Membership Stochastic Blockmodel. - Zheng Yu; Marcin Pietrasik; Marek Z. Reformat (WI, 2019)

Fragmentation Coagulation Based Mixed Membership Stochastic Blockmodel. - Zheng Yu; Xuhui Fan 001; Marcin Pietrasik; Marek Z. Reformat (AAAI, 2020)

A Simple Method for Inducing Class Taxonomies in Knowledge Graphs. - Marcin Pietrasik; Marek Z. Reformat (ESWC, 2020)

Animal Detection in Man-made Environments. - Abhineet Singh; Marcin Pietrasik; Gabriell Natha; Nehla Ghouaiel; Ken Brizel; Nilanjan Ray (WACV, 2020)

Neural Blockmodeling for Multilayer Networks. - Marcin Pietrasik; Marek Z. Reformat (IJCNN, 2021)

Path Based Hierarchical Clustering on Knowledge Graphs. - Marcin Pietrasik; Marek Z. Reformat (CoRR, 2021)

Hierarchical Topic Modelling for Knowledge Graphs. - Yujia Zhang; Marcin Pietrasik; Wenjie Xu; Marek Z. Reformat (ESWC, 2022)

Probabilistic Coarsening for Knowledge Graph Embeddings. - Marcin Pietrasik; Marek Z. Reformat (Axioms, 2023)

Empirical Capacity Model for Self-Attention Neural Networks. - Aki Härmä; Marcin Pietrasik; Anna Wilbik (CoRR, 2024)

Hierarchical Blockmodelling for Knowledge Graphs. - Marcin Pietrasik; Marek Z. Reformat; Anna Wilbik (CoRR, 2024)

Breaking Boundaries Initiative: Workshop on Industry-Academia Collaboration [Technical Activities]. - Marcin Pietrasik; Anna Wilbik; Paul Grefen; Christian Wagner 002; Luis Magdalena (IEEE Comput. Intell. Mag., 2024)

Deep Learning Methods for Detecting Thermal Runaway Events in Battery Production Lines. - Athanasios Athanasopoulos; Matús Mihalák; Marcin Pietrasik (ICPS, 2025)

Predicting the Lifespan of Industrial Printheads with Survival Analysis. - Dan Parii; Evelyne Janssen; Guangzhi Tang; Charalampos Kouzinopoulos; Marcin Pietrasik (ICPS, 2025)