Petra Vidnerová

Petra Vidnerová, née Kudová

Institute of Computer Science, The Czech Academy of Sciences
Pod Vodárenskou věží 2, 182 07 Praha 8, Czech Republic

phone: (+420) 266 053 630
petra cs.cas.cz

[GitHub] [Twitter] [Research Gate] [Google Scholar]

Research interests:

Machine learning, supervised learning, kernel methods, regularization networks. Deep learning.
RBF networks (RBF Layer for Keras).
Hyper-parameter setup, metalearning. Neural architecture search.
Genetic algorithms, evolutionary and hybrid approaches.

Multi-agent network models.

Projects:

22-02067S	AppNeCo: Approximate neurocomputing	Czech Grant Agency	2022 - 2024 (team member)
TS01020123	Optimalizace energetického portfolia pro zvýšení využitelnosti obnovitelných zdrojů	TA ČR	2024 - 2026 (PI)

Past projects:

TN01000024	National Competence Center - Cybernetics and Artificial Intelligence	Technology Agency of the Czech Republic	2019-2022 (team member)
TL04000282	Město pro lidi, ne pro virus	Technology Agency of the Czech Republic	2020/2021 (team member)
18-23827S	Capabilities and Limitations of Shallow and Deep Networks	Czech Grant Agency	2018-6/2021 (team member)
15-18108S	Model complexity of neural, radial, and kernel networks	Czech Grant Agency	2015-2017 (team member)

News:

[6. 11. 2024] Popularizační přednáška na dni otevřených dveří ÚI, P. Vidnerová, G. Kadlecová Co se skrývá za AutoML?.

[19. 9. 2024] Two working papers presented as posters at SBP-BRiMS 2024.
G. Kadlecová, P. Vidnerová, R. Neruda, J.Šlerka. Creating Artificial Survey Panels Is Still Difficult ,
P. Vidnerová, G. Kadlecová, R. Neruda, J. Šlerka. Modelling Information Spread using Generative Agents .

[17. 9. 2024] A conference paper J. Kalina, P. Vidnerová: On the Bayesian Interpretation of Robust Regression Neural Networks at the ICANN 2024 conference.

[26. 6. 2024] Talk Information Spread Modelling Using Generative Agents at CoRE conference, Prague.

[30.5.2024] The paper J. Šíma, J. Cabessa, P. Vidnerová On energy complexity of fully-connected layers was accepted for publication in Neural Networks.

[2. 5. 2024] Paper G. Kadlecová, J. Lukasik, M. Pilát, P. Vidnerová, M. Safari, R. Neruda, F. Hutter Surprisingly Strong Performance Prediction with Neural Graph Features has been accepted to ICML 2024 .

[10. 4. 2024] The join talk with G. Kadlecová Modelling Pitfalls and What Can We Get from LLMs at CoRE Seminar at FF UK.

[19. 3. 2024] The join talk with G. Kadlecová Performance Prediction for NAS at Hora Informaticae Seminar.

[17. 3. 2024] The paper J. Šíma, P. Vidnerová, V. Mrázek: Energy Complexity of Convolutional Neural Networks was accepted for publication in Neural Computation.

[12. 1. 2024] Přednáška Multi-agentní epidemiologické modely při příležitosti návštěvy předsedkyně AV ČR na ÚI.

[9. 1. 2024] The paper J. Kalina, P. Vidnerová, P. Janáček Highly robust training of regularized radial basis function networks was accepted for publication in the journal Kybernetika.

[24. 11. 2023] The presentation The 2022 Election in the United States: How to Verify Reliability of Linear Regression at RELIK 2023 conference.

[9. 11. 2023] The presentation Performance prediction for Neural Architecture Search + poster at DaiZ'23 meetup.

[6. 11. 2023] The paper C. Brom, T. Diviák, J. Drbohlav, V. Korbel, R. Levínský, R. Neruda, G. Suchopárová, J. Šlerka, M. Šmíd, J. Trnka, P. Vidnerová: Rotation-based schedules in elementary schools to prevent COVID-19 spread: A simulation study published in Scientific Reports.

[26. 9. 2023] Presentation Properties of the weighted and robust implicitly weighted correlation coefficients at ICANN 2023 conference.

[24. 9. 2023] Two conference papers in ICANN 2023 conference proceedings:
J. Šíma, P. Vidnerová, V. Mrázek: Energy complexity model for convolutional neural networks.
J. Kalina, P. Vidnerová: Properties of the Weighted and Robust Implicitly Weighted Correlation Coefficients

[8. 9. 2023] Presentation Neural Networks - Energy and Robustness at Jizerka Off-site Seminar.

[7. 9. 2023] The paper Importance of vaccine action and availability and epidemic severity for delaying the second vaccine dose was awarded The Best Result of ICS in 2022 in the category Paper with Application or Social Impact.. Presentation at Jizerka Off-site Seminar.

[23. 5. 2023] Přednáška o modelu M na křtu monografie Rok s pandemií covid-19.

[28. 3. 2023] Paper: L. Berec, T. Diviák, A. Kuběna, R. Levínský, R. Neruda, G. Suchopárová, J. Šlerka, M. Šmíd, J. Trnka, V. Tuček, P. Vidnerová, M. Zajíček:
On the contact tracing for COVID-19: A simulation study .
Published in Epidemics .

[13. 2. 2023] Vyšla monografie Rok s pandemií covid-19 (Reflexe v poločase) .

[6. 12. 2022] Talk at the seminar Hora Informaticae: Model M - an agent-based epidemiological model .

[22. 7. 2022] Presentation at IJCNN conference (WCCI 2022):
J. Kalina, P. Vidnerová, P. Janáček: Sparse Versions of Optimized Centroids .

[24. 6. 2022] Conference paper: G. Suchopárová, P. Vidnerová, R. Neruda, M. Šmíd:
Using a Deep Neural Network in a Relative Risk Model to Estimate Vaccination Protection for COVID-19
Published in Conference proceedings of EANN 2022.

[21. 6. 2022] Paper: L. Berec, J. Smyčka, R. Levínský, E. Hromádková, M. Šoltés, J. Šlerka, V. Tuček, J. Trnka, M. Šmíd, M. Zajíček, T. Diviák, R. Neruda, P. Vidnerová:
Delays, Masks, the Elderly, and Schools: First Covid-19 Wave in the Czech Republic.
Published in Bulletin of Mathematical Biology .

[20. 6. 2022] Presentation at ICAISC 2022 conference:
P. Vidnerová, J. Kalina Multi-objective Bayesian Optimisation for Neural Architecture Search

[10. 5. 2022] Paper: L. Berec, R. Levínský, J. Weiner, M. Šmíd, R. Neruda, P. Vidnerová, G. Suchopárová: Importance of vaccine action and availability and epidemic severity for delaying the second vaccine dose.
Published in Scientific Reports .

[10. 5. 2022] R. Neruda's talk Tested on agents - how we designed an agent-based epidemiological model

2021 - 2019

Curriculum Vitae (pdf) [last update: October, 2024]
PhD Thesis

Old stuff

Diplomka / Diploma thesis (in Czech)

Simple example of learning