Slides
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CoRE conference, June 2024, Prague
Information Spread Modelling using Generative Agents (pdf) -
Seminar of CoRE project, April 2024, Prague
P. Vidnerová, G. Kadlecová, R. Neruda Modelling Pitfalls and What Can We Get from LLMs (pdf) -
Seminar Hora informaticae, March 2024, Prague
P. Vidnerová, G. Kadlecová Performance Prediction for NAS at Hora Informaticae (pdf) -
Návštěva předsedkyně AV ČR na ÚI, Leden 2024, Praha
Multi-agentní epidemiologické modely (pdf) -
RELIK'2023 , November 2023, Prague
J. Kalina, P. Vidnerová, M. Večeř, The 2022 Election in the United States: How to Verify Reliability of Linear Regression (pdf) -
DaiZ'23 meetup, November 2023, Prague
R. Neruda, G. Kadlecová, P. Vidnerová, Performance prediction for Neural Architecture Search (slides, poster) -
ICANN 2023, September 2023, Heraklion
J. Kalina, P. Vidnerová Properties of the weighted and robust implicitly weighted correlation coefficients (pdf) -
Off-site Institute Seminar, September 2023, Jizerka
Vaccination Study Paper and Model M (pdf) -
Off-site Institute Seminar, September 2023, Jizerka
P. Vidnerová Neural Networks - Energy and Robustness (pdf) -
Křest monografie Rok s pandemií covid-19, květen 2023, Praha
P. Vidnerová Model M - an agent-based epidemiological model (pdf) -
Hora Informaticae Seminar, December 2022, Prague
P. Vidnerová Model M - an agent-based epidemiological model (pdf) -
IJCNN (WCCI) 2022, July 2022, Padua
J. Kalina, P. Vidnerová, P. Janáček Sparse Versions of Optimized Centroids (pdf) (poster) -
ICAISC 2022, June 2022, Zakopane
P. Vidnerová, J. Kalina Multi-objective Bayesian Optimization for Neural Architecture Search (pdf) -
RELIK 2021, November 2021, Prague
J. Kalina, P. Vidnerová Application Of Implicitly Weighted Regression Quantiles: Analysis Of The 2018 Czech Presidential Election (pdf) -
ITAT 2021, September 2021, Slovakia
P. Vidnerová, et al. Simulation of non-pharmaceutical interventions in an agent based epidemic model (pdf) -
IWFOS 2021, June 2021, online
J. Kalina, P. Vidnerová On Robust Training of Regression Neural Networks (poster), (slides) -
ICAISC 2021
, June 2021, online
J. Kalina, P. Vidnerová, J. Tichavský A Comparison of Trend Estimators under Heteroscedasticity -
Konference BISOP , červen 2021
Simulace epidemiologických opatření v modelu M (pdf) -
ICAISC 2020 October 2020, Online
Multiobjective evolution for convolutional neural network architecture search (pdf) -
The 14th International Days of Statistics and Economics September 2020, Prague
Least Weighted Absolute Value Estimator with an Application to Investment Data (pdf) -
EANN 2020 June 2020, Online
A Metalearning Study for Robust Nonlinear Regression (pdf) -
Workshop Teorie a praxe statitckého zpracování dat,
Listopad 2019, Nová Seninka
From perceptron to deep neural networks (html), (pdf) -
Den otevřených dveří ÚI, AV ČR, Listopad 2019
Umělá inteligence: dobrý sluha, zlý pán? (pdf) -
AMISTAT 2019 , September 2019,
Liberec
Metalearning for Robust Regression: Sensitivity and Robustification (pdf) -
Výjezdní seminář ÚI, September 2019,
Jizerka
National Competence Center: Artificial Intelligence and Machine Learning (pdf) -
ICAISC 2019, June 2019, Zakopane,
Poster: Robust Training of Radial Basis Function Neural Networks (pdf) -
ITAT 2018 , September 2017, Slovakia
Asynchronous Evolution of Convolutional Networks (pdf) -
ICAISC 2018, June 2018, Zakopane,
Poster: Deep Networks with RBF Layers to Prevent Adversarial Examples (pdf) -
Seminář na UTIA, 2018,
Adversarial examples - vulnerability of machine learning methods and prevention (pdf) -
Seminář Hora Informaticae, 2018,
Evolving Architectures of Deep Neural Networks (pdf) -
Den otevřených dveří ÚI, AV ČR, Listopad 2017
Hluboké neuronové sítě (pptx) -
ITAT 2017 , September 2017, Slovakia
Evolution Strategies for Deep Neural Network Models Design (pdf)
(best paper reward) -
FedCSIS 2017 , September 2017, Prague
Evolution of Keras Architectures for Sensor Data Analysis (pdf) -
Seminář Hora Informaticae, 2016,
Vulnerability of machine learning models to adversarial examples (pdf) - ITAT 2016, September 2016,
Vulnerability of machine learning models to adversarial examples (pdf) - ICAISC 2015, June 2015, Zakopane,
Poster: Product Multi-kernels for Sensor Data Analysis (pdf) - ITAT 2014, September 2014,
Meta-parameters of kernel methods and their optimization (pdf) - Seminář strojového učení,
12. května 2011, Praha MFF UK,
Evolution of Composite Kernel Functions for Regularization Networks (pdf) -
ITAT'2010, Slovakia, 2010
Genetic Algorithm with Species for Regularization Network Metalearning (pdf) -
ICAISC'2010 , Zakopane, June 2010
Hybrid Learning of Regularization Neural Networks (jpg)
- Kognice a umělý život,
Praha, 26.-29.5. 2008:
Emergence chování robotických agentů: neuroevoluce (pdf) - Nové Hrady, popularizační přednáška, 2008:
Neuronové sítě, genetické algoritmy (pdf) -
CIMMACS'07, December 14 - 16, 2007:
Behaviour Patterns Evolution on Individual and Group Level (pdf) - ITAT'2007, Slovakia, September 2007
Learning with Regularization Networks Mixtures (pdf)
Testing different evolutionary neural networks for autonomous robot control (pdf) -
ETID'2007:
Clustering Genetic Algorithm (pdf) -
ZNALOSTI'2007 Ostrava, 2007:
Clustering using Genetic Algorithms (pdf)
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Semantic Web Seminar, Šumava, October 2006:
Learning with Regularization Networks (pdf) - ITAT'2006, Slovakia, September 2006
The Role of Kernel Function in Regularization Network -
ICAISC'2006, Zakopane, June 2006:
Sum and Product Kernel Regularization Networks (pdf) - TAM'2006, Barcelona, June 2006
Learning with Regularization Networks in Bang (pdf) - Syrcodis'06, Moscow,
June 1-2, 20006
Categorical Data Clustering Using Statistical Methods and Neural Networks (pdf) - Department seminar, Šámalova chata,2006:
Learning with kernels and SVM (pdf) - ITAT'2005, Slovakia, September 2005
Learning with Kernel Based Regularization Networks - Edinburgh, seminar talk, June 2, 2005:
Hybrid learning methods in Bang and Regularization Networks (pdf) - ICANGA'2005, Portugal, March 2005
Product Kernel Regularization Network (pdf)
[petra(at)cs.cas.cz]