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Publications

Displaying results 1171 to 1180 of 14717.

  1. 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 Uncertainty in Artificial Intelligence (UAI-2019), July 22-25, Tel Aviv, Israel, Pages 334-344, Proceedings of Machine Learning Research, Vol. 115, AUAI Press, 2019.

  2. 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 Principles and Practice of Knowledge Discovery in Databases (ECML PKDD-2019), International Workshops of ECML PKDD 2019, Proceedings, Part I, September 16-20, Würzburg, Germany, Pages 28-43, Communications in Computer and Information Science, Vol. 1167, Springer, 2019.

  3. 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 Inductive Logic Programming (ILP-2019), September 3-5, Plovdiv, Bulgaria, Pages 62-71, Lecture Notes in Computer Science (LNAI), Vol. 11770, Springer, 2019.

  4. 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 on Machine Learning (ICML-2019), June 9-15, Long Beach, California, USA, Pages 5966-5975, Proceedings of Machine Learning Research, Vol. 97, PMLR, 2019.

  5. Lukas Weber; Lukas Sommer; Julian Oppermann; Alejandro Molina; Kristian Kersting; Andreas Koch

    Resource-Efficient Logarithmic Number Scale Arithmetic for SPN Inference on FPGAs

    In: International Conference on Field-Programmable Technology. International Conference on Field Programmable Technology (FPT-2019), December 9-13, Tianjin, China, Pages 251-254, IEEE, 2019.

  6. Christian Bauckhage; Kristian Kersting; Rafet Sifa; Christian Thurau; Anders Drachen; Alessandro Canossa

    How players lose interest in playing a game: An empirical study based on distributions of total playing times

    In: 2012 IEEE Conference on Computational Intelligence and Games. IEEE Conference on Computational Intelligence and Games (CIG-2012), September 11-14, Granada, Spain, Pages 139-146, IEEE, 2012.

  7. Kristian Kersting; Zhao Xu; Mirwaes Wahabzada; Christian Bauckhage; Christian Thurau; Christoph Römer; Agim Ballvora; Uwe Rascher; Jens Leon; Lutz Plümer

    Pre-Symptomatic Prediction of Plant Drought Stress Using Dirichlet-Aggregation Regression on Hyperspectral Images

    In: Jörg Hoffmann; Bart Selman (Hrsg.). Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence (AAAI-2012), July 22-26, Toronto, Ontario, Canada, Pages 302-308, AAAI Press, 2012.

  8. Christian Bauckhage; Kristian Kersting; Albrecht Schmidt

    Agriculture's Technological Makeover

    In: IEEE Pervasive Computing, Vol. 11, No. 2, Pages 4-7, IEEE, 2012.

  9. Tobias Lang; Marc Toussaint; Kristian Kersting

    Exploration in relational domains for model-based reinforcement learning

    In: Journal of Machine Learning Research, Vol. 13, Pages 3725-3768, JMLR, 2012.

  10. Christian Thurau; Kristian Kersting; Mirwaes Wahabzada; Christian Bauckhage

    Descriptive matrix factorization for sustainability Adopting the principle of opposites

    In: Data Mining and Knowledge Discovery, Vol. 24, No. 2, Pages 325-354, Springer, 2012.

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