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.
Maciej Wołczyk, Bartosz Wójcik, Klaudia Bałazy, Igor Podolak, Jacek Tabor, Marek Śmieja, Tomasz Trzciński
NeurIPS 2021
Maciej Wołczyk, Michał Zając, Razvan Pascanu, Łukasz Kuciński, Piotr Miłoś
NeurIPS 2021
Non-Gaussian Gaussian Processes for Few-Shot Regression
(paper)
Marcin Sendera, Jacek Tabor, Aleksandra Nowak, Andrzej Bedychaj, Massimiliano Patacchiola, Tomasz Trzciński, Przemysław Spurek, Maciej Zięba
NeurIPS 2021
Dawid Rymarczyk, Łukasz Struski, Jacek Tabor, Bartosz Zieliński
SIGKDD 2021
Robust Learning-Augmented Caching: An Experimental Study
(paper)
Jakub Chłędowski, Adam Polak, Bartosz Szabucki, Konrad Żołna
ICML 2021
