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Publications

Displaying results 111 to 120 of 571.

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

    Probabilistic Deep Learning using Random Sum-Product Networks

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/1806.01910, Pages 0-10, arXiv, 2018.

  2. Lukas Sommer; Julian Oppermann; Alejandro Molina; Carsten Binnig; Kristian Kersting; Andreas Koch

    Automatic Mapping of the Sum-Product Network Inference Problem to FPGA-Based Accelerators

    In: 36th IEEE International Conference on Computer Design. IEEE International Conference on Computer Design (ICCD-2018), October 7-10, Orlando, FL, USA, Pages 350-357, IEEE Computer Society, 2018.

  3. Antonio Vergari; Robert Peharz; Nicola Di Mauro; Alejandro Molina; Kristian Kersting; Floriana Esposito

    Sum-Product Autoencoding: Encoding and Decoding Representations Using Sum-Product Networks

    In: Sheila A. McIlraith; Kilian Q. Weinberger (Hrsg.). Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence (AAAI-18), Pages 4163-4170, AAAI Press, 2018.

  4. Alejandro Molina; Antonio Vergari; Nicola Di Mauro; Sriraam Natarajan; Floriana Esposito; Kristian Kersting

    Mixed Sum-Product Networks: A Deep Architecture for Hybrid Domains

    In: Sheila A. McIlraith; Kilian Q. Weinberger (Hrsg.). Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence (AAAI-18), Pages 3828-3835, AAAI Press, 2018.

  5. Michael Benedikt; Kristian Kersting; Phokion G. Kolaitis; Daniel Neider

    Logic and Learning (Dagstuhl Seminar 19361)

    In: Dagstuhl Reports, Vol. 9, No. 9, Pages 1-22, Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik, 2019.

  6. Hitesh Kotte; Milos Kravcik; Nghia Duong-Trung

    Real-Time Posture Correction in Gym Exercises: A Computer Vision-Based Approach for Performance Analysis, Error Classification and Feedback

    In: Khaleel Asyraaf Mat Sanusi; Bibeg Limbu; Jan Schneider; Milos Kravcik; Roland Klemke (Hrsg.). Proceedings of the Third International Workshop on Multimodal Immersive Learning Systems (MILeS 2023). International Workshop on Multimodal Immersive Learning Systems (MILeS-2023), located at Eighteenth European Conference on Technology Enhanced Learning (EC-TEL 2023), September 4-8, Aveiro, Portugal, Pages 64-70, Vol. 3499, CEUR Workshop Proceedings, Aachen, 10/2023.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

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