Evolutionary Learning and Behavior Analysis of the Autonomous Robot Neuro-Controller. - Roman Neruda; Stanislav Slusny; Petra Vidnerová (GEM, 2008)

Comparison of RBF Network Learning and Reinforcement Learning on the Maze Exploration Problem. - Stanislav Slusny; Roman Neruda; Petra Vidnerová (ICANN (1), 2008)

Evolutionary trained radial basis function networks for robot control. - Petra Vidnerová; Stanislav Slusny; Roman Neruda (ICARCV, 2008)

Rule-Based Analysis of Behaviour Learned by Evolutionary and Reinforcement Algorithms. - Stanislav Slusny; Roman Neruda; Petra Vidnerová (ICIC (2), 2008)

Testing Error Estimates for Regularization and Radial Function Networks. - Petra Vidnerová; Roman Neruda (ISNN (1), 2008)

Learning algorithms for small mobile robots: case study on maze exploration. - Stanislav Slusny; Roman Neruda; Petra Vidnerová (ITAT, 2008)

Localization With a Low-cost Robot. - Stanislav Slusny; Roman Neruda; Petra Vidnerová (ITAT, 2009)

Genetic Algorithm with Species for Regularization Network Metalearning. - Roman Neruda; Petra Vidnerová (IAIT, 2010)

Hybrid Learning of Regularization Neural Networks. - Petra Vidnerová; Roman Neruda (ICAISC (2), 2010)

Memetic Evolutionary Learning for Local Unit Networks. - Roman Neruda; Petra Vidnerová (ISNN (1), 2010)

Comparison of behavior-based and planning techniques on the small robot maze exploration problem. - Stanislav Slusny; Roman Neruda; Petra Vidnerová (Neural Networks, 2010)

Evolving Sum and Composite Kernel Functions for Regularization Networks. - Petra Vidnerová; Roman Neruda (ICANNGA (1), 2011)

Evolutionary Learning of Regularization Networks with Multi-kernel Units. - Petra Vidnerová; Roman Neruda (ISNN (1), 2011)

Evolutionary learning of regularization networks with product kernel units. - Petra Vidnerová; Roman Neruda (SMC, 2011)

Product Multi-kernels for Sensor Data Analysis. - Petra Vidnerová; Roman Neruda (ICAISC (1), 2015)

Sensor Data Air Pollution Prediction by Kernel Models. - Petra Vidnerová; Roman Neruda (CCGrid, 2016)

Vulnerability of Machine Learning Models to Adversarial Examples. - Petra Vidnerová; Roman Neruda (ITAT, 2016)

Evolutionary generation of adversarial examples for deep and shallow machine learning models. - Petra Vidnerová; Roman Neruda (MISNC, 2016)

Evolving KERAS Architectures for Sensor Data Analysis. - Petra Vidnerová; Roman Neruda (FedCSIS, 2017)

Evolution Strategies for Deep Neural Network Models Design. - Petra Vidnerová; Roman Neruda (ITAT, 2017)

Deep Networks with RBF Layers to Prevent Adversarial Examples. - Petra Vidnerová; Roman Neruda (ICAISC (1), 2018)

Asynchronous Evolution of Convolutional Networks. - Petra Vidnerová; Roman Neruda (ITAT, 2018)

Robust Training of Radial Basis Function Neural Networks. - Jan Kalina; Petra Vidnerová (ICAISC (1), 2019)

Hitoshi Iba: Evolutionary approach to machine learning and deep neural networks: neuro-evolution and gene regulatory networks - Springer, 2018, Hardcover, 245 pp, ISBN: 978-981-13-0199-5. - Petra Vidnerová (Genet. Program. Evolvable Mach., 2019)

A Metalearning Study for Robust Nonlinear Regression. - Jan Kalina; Petra Vidnerová (EANN, 2020)

Robust Multilayer Perceptrons: Robust Loss Functions and Their Derivatives. - Jan Kalina; Petra Vidnerová (EANN, 2020)

Multiobjective Evolution for Convolutional Neural Network Architecture Search. - Petra Vidnerová; Stepán Procházka; Roman Neruda (ICAISC (1), 2020)

Multi-objective Evolution for Deep Neural Network Architecture Search. - Petra Vidnerová; Roman Neruda (ICONIP (3), 2020)

Vulnerability of classifiers to evolutionary generated adversarial examples. - Petra Vidnerová; Roman Neruda (Neural Networks, 2020)

A Comparison of Trend Estimators Under Heteroscedasticity. - Jan Kalina; Petra Vidnerová; Jan Tichavský (ICAISC (1), 2021)

Simulation of Non-pharmaceutical Interventions in an Agent based Epidemic Model. - Petra Vidnerová; Roman Neruda; Gabriela Suchopárová; Ludek Berec; Tomás Diviák; Ales Kubena; René Levínský; Josef Slerka; Martin Smíd; Jan Trnka; Vít Tucek; Karel Vrbenský; et al. (ITAT, 2021)

Effective Automatic Method Selection for Nonlinear Regression Modeling. - Jan Kalina; Ales Neoral; Petra Vidnerová (Int. J. Neural Syst., 2021)

Using a Deep Neural Network in a Relative Risk Model to Estimate Vaccination Protection for COVID-19. - Gabriela Suchopárová; Petra Vidnerová; Roman Neruda; Martin Smíd (EANN, 2022)

Multi-objective Bayesian Optimization for Neural Architecture Search. - Petra Vidnerová; Jan Kalina (ICAISC (1), 2022)

Sparse Versions of Optimized Centroids. - Jan Kalina; Petra Vidnerová; Patrik Janácek (IJCNN, 2022)

Properties of the Weighted and Robust Implicitly Weighted Correlation Coefficients. - Jan Kalina; Petra Vidnerová (ICANN (9), 2023)

Energy Complexity Model for Convolutional Neural Networks. - Jirí Síma; Petra Vidnerová; Vojtech Mrazek (ICANN (10), 2023)

Surprisingly Strong Performance Prediction with Neural Graph Features. - Gabriela Kadlecová; Jovita Lukasik; Martin Pilát; Petra Vidnerová; Mahmoud Safari; Roman Neruda; Frank Hutter (ICML, 2024)

Highly robust training of regularized radial basis function networks. - Jan Kalina; Petra Vidnerová; Patrik Janácek (Kybernetika, 2024)

Energy Complexity of Convolutional Neural Networks. - Jirí Síma; Petra Vidnerová; Vojtech Mrazek (Neural Comput., 2024)

On energy complexity of fully-connected layers. - Jirí Síma; Jérémie Cabessa; Petra Vidnerová (Neural Networks, 2024)