Publications

Kristian Kersting; Miryung Kim; Guy Van den Broeck; Thomas Zimmermann

SE4ML - Software Engineering for AI-ML-based Systems (Dagstuhl Seminar 20091)

In: Dagstuhl Reports, Vol. 10, No. 2, Pages 76-87, Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik, 2020.

Johannes Czech; Patrick Korus; Kristian Kersting

Monte-Carlo Graph Search for AlphaZero

In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2012.11045, Pages 0-10, arXiv, 2020.

Christopher Morris; Nils M. Kriege; Franka Bause; Kristian Kersting; Petra Mutzel; Marion Neumann

TUDataset: A collection of benchmark datasets for learning with graphs

In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2007.08663, Pages 0-10, arXiv, 2020.

Srijita Das; Sriraam Natarajan; Kaushik Roy; Ronald Parr; Kristian Kersting

Fitted Q-Learning for Relational Domains

In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2006.05595, Pages 0-10, arXiv, 2020.

Patrick Schramowski; Wolfgang Stammer; Stefano Teso; Anna Brugger; Xiaoting Shao; Hans-Georg Luigs; Anne-Katrin Mahlein; Kristian Kersting

Right for the Wrong Scientific Reasons: Revising Deep Networks by Interacting with their Explanations

In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2001.05371, Pages 0-10, arXiv, 2020.

Fabrizio Ventola; Karl Stelzner; Alejandro Molina; Kristian Kersting

Residual Sum-Product Networks

In: Manfred Jaeger; Thomas Dyhre Nielsen (Hrsg.). Proceedings of the 10th International Conference on Probabilistic Graphical Models. International Conference on Probabilistic Graphical Models (PGM-2020), September 23-25, Aalborg, Denmark, Pages 545-556, Proceedings of Machine Learning Research, Vol. 138, PMLR, 2020.

Xiaoting Shao; Alejandro Molina; Antonio Vergari; Karl Stelzner; Robert Peharz; Thomas Liebig; Kristian Kersting

Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures

In: Manfred Jaeger; Thomas Dyhre Nielsen (Hrsg.). Proceedings of the 10th International Conference on Probabilistic Graphical Models. International Conference on Probabilistic Graphical Models (PGM-2020), September 23-25, Aalborg, Denmark, Pages 401-412, Proceedings of Machine Learning Research, Vol. 138, PMLR, 2020.