Retreat Siegmundsburg 2022

• Date: September 26th to 30th, 2022
• Place: Haus Rosenbaum, Hiftenberg 3, 98724 Neuhaus am Rennweg / OT Siegmundsburg
• Program: https://indico.rz.uni-jena.de/event/28/

Paper Discussion Groups

On Tuesday and Thursday, we are working in groups, discussing publications that are related to topics of the research training group. Both days end with a short presentation on results. Groups 1 to 6 meet on Tuesday, and Groups 7 to 12 on Thursday.

1. Tensor-tensor products: Misha Kilmer et al.: https://arxiv.org/pdf/2001.00046.pdf

   • Alex Breuer, Christoph Staudt, Niklas Merk, Paul Gerhardt Rump, Torsten Bosse

2. A Bayesian machine scientist: Roger Guimerà et al.: https://www.science.org/doi/10.1126/sciadv.aav6971

   • Henrik Voigt, Martin Bücker, Paul Kahlmeyer, Pepe Eulzer, Shantanu Pramod Kodgirwar

3. Maximum entropy principle: Adom Giffin: https://arxiv.org/pdf/0901.2987.pdf

   • Brian Zahoransky, Joachim Giesen, Michael Habeck, Tim Hoffmann, Wolfhart Feldmeier

4. Probabilistic theorem proving: V. Gogate and P. Domingos: Probabilistic Theorem Proving: https://arxiv.org/pdf/1202.3724.pdf

   • Andreas Goral, Olaf Beyersdorff, Luc Spachmann, Stefan Perko, Steffen Meier

5. Graph Neural Networks as Fast Global Search Heuristics: - Jan Tönshoff et al.: https://arxiv.org/pdf/2208.10227.pdf

   • Agnes Schleitzer, Benjamin Böhm, Julien Klaus, Matthias Mitterreiter, Meena Mahajan

6. Inside-Outside and Forward-Backward Algorithms Are Just Backprop: Jason Eisner: https://aclanthology.org/W16-5901.pdf

   • Andreas Kröpelin, Christian Hoener zu Siederdissen, Johannes Schoder, Shima Baniadamdizaj, Vincent Messow

7. The frontier of simulation-based inference: Kyle Cranmer, Johann Brehmer, and Gilles Louppe: https://arxiv.org/pdf/1911.01429.pdf

   • Johannes Schoder, Martin Bücker, Michael Habeck, Pepe Eulzer, Vincent Messow

8. Causality for Machine Learning: Bernhard Schölkopf: https://arxiv.org/pdf/1911.10500.pdf

   • Andreas Goral, Andreas Kröpelin, Meena Mahajan, Olaf Beyersdorff, Wolfhart Feldmeier

9. Sampling can be faster than optimization: Yi-An Ma et al.: https://www.pnas.org/doi/epdf/10.1073/pnas.1820003116

   • Benjamin Böhm, Brian Zahoransky, Christian Hoener zu Siederdissen, Luc Spachmann, Shantanu Pramod Kodgirwar

10. Lectures on Randomized Numerical Linear Algebra: Petros Drineas and Michael W. Mahoney: https://arxiv.org/pdf/1712.08880.pdf

    • Julien Klaus, Niklas Merk, Shima Baniadamdizaj, Stefan Perko, Steffen Meier

11. Towards Learning Quantifier Instantiation in SMT: Mikolás Janota et al.: https://drops.dagstuhl.de/opus/volltexte/2022/16681/pdf/LIPIcs-SAT-2022-7.pdf

    • Agnes Schleitzer, Christoph Staudt, Joachim Giesen, Paul Kahlmeyer, Tim Hoffmann

12. Tensor comprehensions: Nicolas Vasilache et al.: https://arxiv.org/pdf/1802.04730.pdf

    • Alex Breuer, Henrik Voigt, Matthias Mitterreiter, Paul Gerhardt Rump, Torsten Bosse