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  1. Benjamin Hilprecht; Carsten Binnig; Uwe Röhm

    Learning a Partitioning Advisor with Deep Reinforcement Learning

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/1904.01279, Pages 0-10, arXiv, 2019.

  2. Muhammad El-Hindi; Martin Heyden; Carsten Binnig; Ravi Ramamurthy; Arvind Arasu; Donald Kossmann

    BlockchainDB - Towards a Shared Database on Blockchains

    In: Peter A. Boncz; Stefan Manegold; Anastasia Ailamaki; Amol Deshpande; Tim Kraska (Hrsg.). Proceedings of the 2019 International Conference on …

  3. Alex Galakatos; Michael Markovitch; Carsten Binnig; Rodrigo Fonseca; Tim Kraska

    FITing-Tree: A Data-aware Index Structure

    In: Peter A. Boncz; Stefan Manegold; Anastasia Ailamaki; Amol Deshpande; Tim Kraska (Hrsg.). Proceedings of the 2019 International Conference on …

  4. Patrick Schramowski; Cigdem Turan; Sophie F. Jentzsch; Constantin A. Rothkopf; Kristian Kersting

    BERT has a Moral Compass: Improvements of ethical and moral values of machines

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/1912.05238, Pages 0-10, arXiv, 2019.

  5. Fabrizio Ventola; Karl Stelzner; Alejandro Molina; Kristian Kersting

    Random Sum-Product Forests with Residual Links

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/1908.03250, Pages 0-10, arXiv, 2019.

  6. Alejandro Molina; Antonio Vergari; Karl Stelzner; Robert Peharz; Pranav Subramani; Nicola Di Mauro; Pascal Poupart; Kristian Kersting

    SPFlow: An Easy and Extensible Library for Deep Probabilistic Learning using Sum-Product Networks

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/1901.03704, Pages 0-10, arXiv, 2019.

  7. Robert Peharz; Antonio Vergari; Karl Stelzner; Alejandro Molina; Martin Trapp; Xiaoting Shao; Kristian Kersting; Zoubin Ghahramani

    Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning

    In: Amir Globerson; Ricardo Silva (Hrsg.). Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence. Conference in …

  8. Claas Völcker; Alejandro Molina; Johannes Neumann; Dirk Westermann; Kristian Kersting

    DeepNotebooks: Deep Probabilistic Models Construct Python Notebooks for Reporting Datasets

    In: Peggy Cellier; Kurt Driessens (Hrsg.). Machine Learning and Knowledge Discovery in Databases. European Conference on Machine Learning and …

  9. Navdeep Kaur; Gautam Kunapuli; Saket Joshi; Kristian Kersting; Sriraam Natarajan

    Neural Networks for Relational Data

    In: Dimitar Kazakov; Can Erten (Hrsg.). Inductive Logic Programming - 29th International Conference, Proceedings. International Conference on …

  10. Karl Stelzner; Robert Peharz; Kristian Kersting

    Faster Attend-Infer-Repeat with Tractable Probabilistic Models

    In: Kamalika Chaudhuri; Ruslan Salakhutdinov (Hrsg.). Proceedings of the 36th International Conference on Machine Learning. International Conference …