GMUM (Group of Machine Learning Research) is a group at Jagiellonian University working on various aspects of machine learning, and in particular deep learning - in both fundamental and applied setting. The group is led by prof. Jacek Tabor.
Some of the research directions our group pursues include:
- generative models: efficient training and sampling; inpainting; super-resolution,
- theoretical understanding of deep learning and optimization,
- natural language processing,
- drug design and cheminformatics,
- unsupervised learning and clustering,
- computer vision and medical image analysis.
Dawid Rymarczyk, Adriana Borowa, Jacek Tabor, Bartosz Zieliński
WACV 2021
Combination of Molecular Simulation and Deep Learning for De Novo Drug Design
(grant)
Tomasz Danel
Preludium 19
Szymon Knop, Jacek Tabor, Przemysław Spurek, Igor Podolak, Marcin Mazur, Stanisław Jastrzębski
JMLR 2020
Bartosz Wójcik, Maciej Wołczyk, Klaudia Bałazy, Jacek Tabor
ECML PKDD 2020
Przemysław Spurek, Sebastian Winczowski, Jacek Tabor, Maciej Zamorski, Maciej Zięba, Tomasz Trzciński
ICML 2020
Transformer-based methods for novel active chemical compounds
(grant)
Łukasz Maziarka
Preludium 2020
Krzysztof Maziarz, Mingxing Tan, Andrey Khorlin, Marin Georgiev, Andrea Gesmundo
ICML Workshop on AutoML 2019; 1st place in Data Science Masters - best Master's thesis competition, Applied track
Jacek Tabor
2019-2023, FNP TEAM-NET