2017/18 Seminar Machine Learning for Physicists, by Florian Marquardt

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This seminar is a follow-up to the lecture of the summer term (see lecture homepage).

Students will be asked to present modern research articles on machine learning, especially those that address the application of machine learning techniques to questions in physics (and in the natural sciences in general).

  • Tentative schedule: Mondays, 18:00-20:00 (I'm choosing this slot such that a maximum number of students may participate if they like to)
  • First meeting: Monday, October 23.
  • Where: Lecture hall F
  • Also look for the studon-group
  • Lecturer/Advisor: Florian.Marquardt@fau.de

Preliminary Schedule:

  • 30.10.: Florian Unger, Neural Turing Machine
  • 13.11.: Matthias Zürl, Go
  • 20.11.: Alexander Blania, Inverse Imaging or Bell Inequalities
  • 27.11.: Manyu Wen, Neural Hybrid Computing
  • 6.12. (Wednesday!): Tim Stüven, Predicting Dynamics of 2D objects or Bell inequalities & Ankan Bag, Coherent Nanophotonic Circuits
  • 18.12.: Bystrik Matas, Renormalization Group and Neural Networks or Quantum Many-Body Dynamics
  • 15.1.: Philip Thalhammer, Detection of Gravitational Lensing
  • 22.1.: David Böhringer, Toxic Materials or Face of Crystals & Felix Lammermann, Superconducting Transition Temperatures
  • 29.1.: Jasmin Graf, Active Learning for Quantum Experiments
  • 7.2. (Wednesday!): Timo Niehoff, Phase Transitions by Confusion and Sourav Chatterjee (topic to be determined)