Helping AI to Play Hearthstone using Neural Networks. - Lukasz Grad (FedCSIS, 2017)

Toward Machine Learning on Granulated Data - a Case of Compact Autoencoder-based Representations of Satellite Images. - Mateusz Przyborowski; Tomasz Tajmajer; Lukasz Grad; Andrzej Janusz; Piotr Biczyk; Dominik Slezak (IEEE BigData, 2018)

Toward an Intelligent HS Deck Advisor: Lessons Learned from AAIA'18 Data Mining Competition. - Andrzej Janusz; Tomasz Tajmajer; Maciej Swiechowski; Lukasz Grad; Jacek Puczniewski; Dominik Slezak (FedCSIS, 2018)

Utilizing Hybrid Information Sources to Learn Representations of Cards in Collectible Card Video Games. - Andrzej Janusz; Lukasz Grad; Dominik Slezak (ICDM Workshops, 2018)

Clash Royale Challenge: How to Select Training Decks for Win-rate Prediction. - Andrzej Janusz; Lukasz Grad; Marek Grzegorowski (FedCSIS, 2019)

Integrated Human Tracking Based on Video and Smartphone Signal Processing within the Arahub System. - Jan Ludziejewski; Lukasz Grad; Lukasz Przebinda; Tomasz Tajmajer (FedCSIS, 2020)

Learning multimodal entity representations and their ensembles, with applications in a data-driven advisory framework for video game players. - Andrzej Janusz; Daniel Kaluza; Maciej Matraszek; Lukasz Grad; Maciej Swiechowski; Dominik Slezak (Inf. Sci., 2022)

Single-Stage Uncertainty-Aware Jersey Number Recognition in Soccer. - Lukasz Grad (CVPR Workshops, 2025)