Journal articles

  1. Wojtak, W., Ferreira, F., Louro, L., Bicho, E., & Erlhagen, W. (2023). Adaptive timing in a dynamic field architecture for natural human-robot interactions. Cognitive Systems Research, 82, 101148. PDF BibTeX
  2. Wojtak, W., Coombes, S., Avitabile, D., Bicho, E., & Erlhagen, W. (2023). Robust working memory in a two-dimensional continuous attractor network. Cognitive Neurodynamics, 1-17. PDF BibTeX
  3. Wojtak, W., Coombes, S., Avitabile, D., Bicho, E., & Erlhagen, W. (2021). A dynamic neural field model of continuous input integration. Biological Cybernetics, 115(5), 451-471. PDF BibTeX
  4. Wojtak, W., Ferreira, F., Vicente, P., Louro, L., Bicho, E., & Erlhagen, W. (2020). A neural integrator model for planning and value-based decision making of a robotics assistant. Neural Computing and Applications 33(8), 3737-3756. PDF BibTeX
  5. Ferreira, F., Wojtak, W., Sousa, E., Louro, L., Bicho, E., & Erlhagen, W. (2020). Rapid learning of complex sequences with time constraints: A dynamic neural field model. IEEE Transactions on Cognitive and Developmental Systems, 13, 853-864. PDF BibTeX
  6. Wojtak, W., Silva, C. J., & Torres, D. F. (2018). Uniform asymptotic stability of a fractional tuberculosis model. Mathematical Modelling of Natural Phenomena, 13(1), 9. PDF BibTeX

Conference proceedings

  1. Wojtak, W., Bicho, E. & Erlhagen, W. (2023). Solving Neural Field Equations using Physics Informed Neural Networks . In International Conference of Numerical Analysis and Applied Mathematics. PDF
  2. Barbosa, P., Ferreira, F., Fernandes, C., Erlhagen, W., Guimarães, P., Wojtak, W., Monteiro, S., & Bicho, E. (2022). Endowing intelligent vehicles with the ability to learn user’s habits and preferences with machine learning methods. In International Conference on Intelligent Data Engineering and Automated Learning (pp. 157-169). Springer, Cham. BibTeX
  3. Wojtak, W., Ferreira, F., Guimarães , P., Barbosa, P., Monteiro, S., Erlhagen, W., & Bicho, E. (2021). Towards endowing intelligent cars with the ability to learn the routines of multiple drivers: a dynamic neural field model. In International Conference on Computational Science and Its Applications (pp. 337-349). Springer, Cham. PDF BibTeX
  4. Ferreira, F., Wojtak, W., Fernandes, C., Guimarães, P., Monteiro, S., Bicho, E., & Erlhagen, W. (2021). Dynamic identification of stop locations from GPS trajectories based on their temporal and spatial characteristics. In International Conference on Artificial Neural Networks (pp. 347-359). Springer, Cham. BibTeX
  5. Wojtak, W., Ferreira, F., Bicho, E., & Erlhagen, W. (2019). Neural field model for measuring and reproducing time intervals. In International Conference on Artificial Neural Networks (pp. 327-338). Springer, Cham. PDF BibTeX
  6. Wojtak, W., Ferreira, F., Bicho, E., & Erlhagen, W. (2019). Numerical analysis of the shape of bump solutions in a neuronal model of working memory. In AIP Conference Proceedings (Vol. 2116, No. 1, p. 250003). AIP Publishing LLC. PDF BibTeX
  7. Wojtak, W., Ferreira, F., Louro, L., Bicho, E., & Erlhagen, W. (2017). Towards temporal cognition for robots: a neurodynamics approach. In 2017 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) (pp. 407-412). IEEE. PDF BibTeX
  8. Wojtak, W., Coombes, S., Bicho, E., & Erlhagen, W. (2016). Combining spatial and parametric working memory in a dynamic neural field model. In International Conference on Artificial Neural Networks (pp. 411-418). Springer, Cham. PDF BibTeX
  9. Wojtak, W., Ferreira, F., Erlhagen, W., & Bicho, E. (2015). Learning joint representations for order and timing of perceptual-motor sequences: a dynamic neural field approach. In 2015 International Joint Conference on Neural Networks (IJCNN) (pp. 1-7). IEEE. PDF BibTeX
  10. Filipczuk, P., Wojtak, W., & Obuchowicz, A. (2012). Automatic nuclei detection on cytological images using the firefly optimization algorithm. In Information Technologies in Biomedicine (pp. 85-92). Springer, Berlin, Heidelberg. PDF BibTeX

Thesis

  1. Wojtak, W. (2021). A novel dynamic field model supporting a continuum of bump amplitudes: Analysis and Applications. PhD Thesis, University of Minho. PDF BibTeX