Bio-inspired artificial neural networks

Foundation for Polish Science (FNP)
TEAM-NET programme

Our Project

The artificial neural network model was created based on analogies to biological counterparts, such as a simplified model of the neuron or a system of retinal neurons. Due to the increasing complexity of tasks and problems with the development of effective methods for learning deep neural networks, solutions based on algebraic structures dominate Today, advanced approaches in machine learning such as deep learning show a number of undesirable features, such as forgetfulness, susceptibility to adversarial examples, the requirement for a large training set, and slow learning. Most of these features do not occur in biological systems, thus it would be beneficial to take an inspiration from them to help training artificial systems. The aim of the project is to analyze high-level behaviors of biological neural systems and to build innovative artificial models by proposing new paradigms of learning and new architectures of computational models.

Job offers

The Jagiellonian University will run six research groups: Cognitive group (leader Tadeusz Marek), Physics group (leader Maciej A. Nowak), Machine-learning group, Neuro group, BioDataScience group, InfoTech group.

Job offers for

Cognitive group:

Physics group:

Machine-learning group:

Neuro group:

BioDataScience group:

InfoTech group:

are open.

If you are interested in applying, please fill out the following recruitment form (DOC) or (PDF).

Specific recruitment rules are available here. Declaration on intellectual is available here. The form for processing personal data can be found here.

Business contacts

Seminars Schedule

2019
2020

17th December

Maria Lewandowska, "Głębokie konwolucyjne sieci neuronowe do analizy skanów MRI"

10th December

Dyskusja na temat danych pochodzących od grupy kongnitywistycznej

3rd December

Anna Ceglarek i Bartosz Bohaterewicz, "Zastosowanie teorii grafów w analizach fMRI"

5th November

Group Workshop

11:00 - 12:00	Machine-learning group
12:10 - 13:10	Physics group
13:10 - 14:00	Lunch
14:00 - 15:00	Neuro group
15:10 - 16:10	Cognitive group
16:10 - 16:40	Coffee Break
16:40 - 18:40	Group Discussion

Localization: Room 1146 (first floor). Faculty of Mathematics and Computer Science, Łojasiewicza 6, 30-348 Kraków.

24th September

Maciej Wołczyk, Jacek Tabor, Marek Śmieja, "Biologically-Inspired Spatial Neural Networks"

10th September

Romuald Janik, "Explaining the Human Visual Brain 2019 competition and workshop"
Additional information: Paper you can find here.

30th July

Magda Gawłowska, "EEG 101"

9th July

Igor Podolak, "BioNN machine learning"

31th March

Group Workshop

10:00 - 11:00	Jacek Rogala: “Sztuczne sieci neuronowe z perspektywy biologa”
11:00 - 12:00	Daniel Wójcik “Równania Hodgkina-Huxleya - mechanizmy generacji iglicy”
12:00 - 13:30	Lunch
13:30 - 14:30	Tomasz Trzciński "Przegląd propozycji mini-projektów w grupie InfoTech"
14:30 - 15:30	Magda Gawłowska "Aktualne trendy w analizie danych EEG"
15:30 - 16:00	Jacek Tabor: dyskusja

Localization: online meeting

3rd March

Marek Śmieja, "Direct Feedback Alignment"

18th February

Group Workshop

11:00 - 12:00	Przemysław Spurek: Independent Component Analysis
12:00 - 13:00	Lunch
13:00 - 14:30	Paweł Hottowy: Perspektywy budowy zaawansowanego implantu dla niewidomych
14:30 - 15:30	Coffee Break: Room 1103
15:30 - 17:00	Daniel Wójcik: Wstęp do neurobiologii obliczeniowej, cz. 1: Równanie kabla - dendryty bierne

Localization: Room 1016 (first floor). Faculty of Mathematics and Computer Science, Łojasiewicza 6, 30-348 Kraków.

28th January

Igor Sieradzki, Maciej Wołczyk: Continual Machine Learning: Scenarios, Current Methods and Evaluation

21st January

Group Workshop

12:00 - 14:00	Igor Podolak, Igor Sieradzki, Maciej Wołczyk: Introduction to continual learning
14:00 - 14:45	Lunch
14:45 - 15:30	Tomasz Trzciński: Learning binary representaiton of images
15:30 - 16:15	Paweł Oświęcimka: Fractal approach to time series analysis
16:15 - 16:45	Coffee break
16:45 - 17:30	Ziemowit Sławiński: Spiking neural networks