Profile of Robert Sicks

Fields of Activity/Competences

  • Time series analysis and forecasting 
  • Validation models and algorithms for structured products and derivatives 
  • Machine Learning Methods
  • Monte-Carlo methods, especially Multilevel and Markov chain
  • Neural Networks/Deep Learning


Major Publications

  • Sicks, R.; Korn, R.; Schwaar, S.:
    A Generalised Linear Model Framework for β-Variational Autoencoders based on Exponential Dispersion Families.
    Journal of Machine Learning Research, Volume 22, Pages 1-41, (2021).
  • Sicks, R.; Korn, R.; Schwaar, S.:
    A lower bound for the ELBO of the Bernoulli Variational Autoencoder.
    arXiv:2003.11830, (2020).
  • Sicks, R.: Gauß-Newton and M-Estimators for ARMA-Processes with regularly varying tails.
    Masterthesis, KIT Karlsruhe, (2016).