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Petra Vidnerová
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2020 – today
- 2024
- [j5]Jirí Síma, Jérémie Cabessa
, Petra Vidnerová
On energy complexity of fully-connected layers. Neural Networks 178: 106419 (2024) - [c34]Gabriela Kadlecová, Jovita Lukasik, Martin Pilát, Petra Vidnerová, Mahmoud Safari, Roman Neruda, Frank Hutter:
Surprisingly Strong Performance Prediction with Neural Graph Features. ICML 2024 - [i1]Gabriela Kadlecová, Jovita Lukasik, Martin Pilát, Petra Vidnerová, Mahmoud Safari, Roman Neruda, Frank Hutter:
Surprisingly Strong Performance Prediction with Neural Graph Features. CoRR abs/2404.16551 (2024) - 2023
- [c33]Jirí Síma, Petra Vidnerová
Energy Complexity Model for Convolutional Neural Networks. ICANN (10) 2023: 186-198 - [c32]Jan Kalina, Petra Vidnerová:
Properties of the Weighted and Robust Implicitly Weighted Correlation Coefficients. ICANN (9) 2023: 200-212 - 2022
- [c31]Gabriela Suchopárová
Using a Deep Neural Network in a Relative Risk Model to Estimate Vaccination Protection for COVID-19. EANN 2022: 310-320 - [c30]Petra Vidnerová
Multi-objective Bayesian Optimization for Neural Architecture Search. ICAISC (1) 2022: 144-153 - [c29]Jan Kalina
Sparse Versions of Optimized Centroids. IJCNN 2022: 1-7 - 2021
- [j4]Jan Kalina
Effective Automatic Method Selection for Nonlinear Regression Modeling. Int. J. Neural Syst. 31(10): 2150020:1-2150020:12 (2021) - [c28]Jan Kalina
A Comparison of Trend Estimators Under Heteroscedasticity. ICAISC (1) 2021: 89-98 - [c27]Petra Vidnerová, Roman Neruda, Gabriela Suchopárová, Ludek Berec, Tomás Diviák, Ales Kubena, René Levínský, Josef Slerka, Martin Smíd, Jan Trnka, Vít Tucek, Karel Vrbenský, Milan Zajícek:
Simulation of Non-pharmaceutical Interventions in an Agent based Epidemic Model. ITAT 2021: 263-268 - 2020
- [j3]Petra Vidnerová
Vulnerability of classifiers to evolutionary generated adversarial examples. Neural Networks 127: 168-181 (2020) - [c26]Jan Kalina
A Metalearning Study for Robust Nonlinear Regression. EANN 2020: 499-510 - [c25]Jan Kalina
Robust Multilayer Perceptrons: Robust Loss Functions and Their Derivatives. EANN 2020: 546-557 - [c24]Petra Vidnerová
Multiobjective Evolution for Convolutional Neural Network Architecture Search. ICAISC (1) 2020: 261-270 - [c23]Petra Vidnerová
Multi-objective Evolution for Deep Neural Network Architecture Search. ICONIP (3) 2020: 270-281
2010 – 2019
- 2019
- [j2]Petra Vidnerová
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. Genet. Program. Evolvable Mach. 20(2): 151-153 (2019) - [c22]Jan Kalina
Robust Training of Radial Basis Function Neural Networks. ICAISC (1) 2019: 113-124 - 2018
- [c21]Petra Vidnerová
Deep Networks with RBF Layers to Prevent Adversarial Examples. ICAISC (1) 2018: 257-266 - [c20]Petra Vidnerová, Roman Neruda:
Asynchronous Evolution of Convolutional Networks. ITAT 2018: 80-85 - 2017
- [c19]Petra Vidnerová, Roman Neruda
Evolving KERAS Architectures for Sensor Data Analysis. FedCSIS 2017: 109-112 - [c18]Petra Vidnerová, Roman Neruda:
Evolution Strategies for Deep Neural Network Models Design. ITAT 2017: 159-166 - 2016
- [c17]Petra Vidnerová, Roman Neruda
Sensor Data Air Pollution Prediction by Kernel Models. CCGrid 2016: 666-673 - [c16]Petra Vidnerová, Roman Neruda:
Vulnerability of Machine Learning Models to Adversarial Examples. ITAT 2016: 187-194 - [c15]Petra Vidnerová, Roman Neruda
Evolutionary generation of adversarial examples for deep and shallow machine learning models. MISNC 2016: 43 - 2015
- [c14]Petra Vidnerová
Product Multi-kernels for Sensor Data Analysis. ICAISC (1) 2015: 123-133 - 2011
- [c13]Petra Vidnerová
Evolving Sum and Composite Kernel Functions for Regularization Networks. ICANNGA (1) 2011: 180-189 - [c12]Petra Vidnerová
Evolutionary Learning of Regularization Networks with Multi-kernel Units. ISNN (1) 2011: 538-546 - [c11]Petra Vidnerová
Evolutionary learning of regularization networks with product kernel units. SMC 2011: 638-643 - 2010
- [j1]Stanislav Slusny, Roman Neruda
Comparison of behavior-based and planning techniques on the small robot maze exploration problem. Neural Networks 23(4): 560-567 (2010) - [c10]Roman Neruda
Genetic Algorithm with Species for Regularization Network Metalearning. IAIT 2010: 192-201 - [c9]Petra Vidnerová
Hybrid Learning of Regularization Neural Networks. ICAISC (2) 2010: 124-131 - [c8]Roman Neruda
Memetic Evolutionary Learning for Local Unit Networks. ISNN (1) 2010: 534-541
2000 – 2009
- 2009
- [c7]Stanislav Slusny, Roman Neruda, Petra Vidnerová:
Localization With a Low-cost Robot. ITAT 2009: 77-80 - 2008
- [c6]Roman Neruda, Stanislav Slusny, Petra Vidnerová:
Evolutionary Learning and Behavior Analysis of the Autonomous Robot Neuro-Controller. GEM 2008: 222-228 - [c5]Stanislav Slusny, Roman Neruda
Comparison of RBF Network Learning and Reinforcement Learning on the Maze Exploration Problem. ICANN (1) 2008: 720-729 - [c4]Petra Vidnerová, Stanislav Slusny, Roman Neruda
Evolutionary trained radial basis function networks for robot control. ICARCV 2008: 833-838 - [c3]Stanislav Slusny, Roman Neruda
Rule-Based Analysis of Behaviour Learned by Evolutionary and Reinforcement Algorithms. ICIC (2) 2008: 284-291 - [c2]Petra Vidnerová
Testing Error Estimates for Regularization and Radial Function Networks. ISNN (1) 2008: 549-554 - [c1]Stanislav Slusny, Roman Neruda, Petra Vidnerová:
Learning algorithms for small mobile robots: case study on maze exploration. ITAT 2008
Coauthor Index
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last updated on 2024-10-23 21:23 CEST by the dblp team
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