Group of Machine Learning Research

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:

Recent achievements

Finding the Optimal Network Depth in Classification Tasks (paper)

Bartosz Wójcik, Maciej Wołczyk, Klaudia Bałazy, Jacek Tabor

Hypernetwork approach to generating point clouds (paper)

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

Evolutionary-Neural Hybrid Agents for Architecture Search (paper)

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

Bio-inspired artificial neural networks (grant)

Jacek Tabor
2019-2023, FNP TEAM-NET

The Break-Even Point on the Optimization Trajectories of Deep Neural Networks (paper)

Stanisław Jastrzębski, Maciej Szymczak, Stanislav Fort, Devansh Arpit, Jacek Tabor, Kyunghyun Cho*, Krzysztof Geras*
ICLR 2020 (Spotlight)

Persistence bag of words for topological data analysis (paper)

Bartosz Zieliński, Michał Lipiński, Mateusz Juda, Matthias Zeppelzauer, Paweł Dłotko
IJCAI 2019

Parameter-Efficient Transfer Learning for NLP (paper)

Neil Houlsby, Andrei Giurgiu, Stanisław Jastrzębski, Bruna Morrone, Quentin de Laroussilhe, Andrea Gesmundo, Mona Attariyan, Sylvain Gelly
ICML 2019

Contact Us

Group of Machine Learning Research
Faculty of Mathematics and Computer Science
ul. Lojasiewicza 6
30-342, Cracow, Poland