Hierarchical methods
Positions: Student Researcher
Created: 2023-10-22 Deadline:
Location: Poland
Neural networks achieve very good results in typical classification and clustering tasks. However, the interpretation of the obtained results is limited. In this project, we aim to focus on constructing deep models that make predictions by undertaking a sequence of decisions.
Intuitively, we are dealing with models that build a decision tree/graph, allowing for an enhanced interpretation of the results. A model has already been implemented and detailed in the https://arxiv.org/abs/2107.13214.
General must-have requirements
The student needs to know how to program in both tensorflow and pytorch (In order to undestand the present code and implement new methods).
Contact: Marek Śmieja (marek.smieja [ at ] ii.uj.edu.pl)
Project's lab:
GMUM (Group of Machine Learning Research) is a group of researchers working on various aspects of machine learning, and in particular deep learning - in both fundamental and applied settings. The group is led by prof. Jacek Tabor. We are based in the Jagiellonian University in the beautiful city of Kraków, Poland.
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.
In 2023, we organized the second edition of Machine Learning Summer School (MLSS^S) with a focus on Applications in Science. We invite participants to collaborate with us on various ongoing research projects - learn more here.
See lab's page