Tobias Pielok

About

I started as a PhD student at the chair of Statistical Learning and Data Science in the Department of Statistics at the LMU Munich on October 2020. My research focus is on Bayesian deep learning and model-based optimization.

I have a Bachelor's Degree (B.Sc.) in Statistics from the LMU Munich and a Bachelor's Degree (B.Sc.) in Mechanical Engineering from the TU Munich and a Master's Degree (M.Sc.) in Mechanical Engineering from the TU Munich.

Contact

Institut für Statistik

Ludwig-Maximilians-Universität München

Ludwigstraße 33

D-80539 München

Tobias.Pielok [at] stat.uni-muenchen.de

You Can Find me on

References

  1. Pielok T, Bischl B, Rügamer D (2023) Approximate Bayesian Inference with Stein Functional Variational Gradient Descent International Conference on Learning Representations,
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  2. Karl F, Pielok T, Moosbauer J, Pfisterer F, Coors S, Binder M, Schneider L, Thomas J, Richter J, Lang M, Garrido-Merchán EC, Branke J, Bischl B (2022) Multi-Objective Hyperparameter Optimization – An Overview.
    link | pdf    .
  3. Bischl B, Binder M, Lang M, Pielok T, Richter J, Coors S, Thomas J, Ullmann T, Becker M, Boulesteix A-L, Deng D, Lindauer M (2021) Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges. arXiv preprint arXiv:2107.05847.
    link | pdf    .
  4. Schulz O, Pielok T, Szalay M, RCS-77, Beaujean F, kevin-kroeninger, Cornelius-G (2019) bat/BAT.jl: BAT.jl v0.2.1. https://doi.org/10.5281/zenodo.2605312.