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Publications

Displaying results 491 to 500 of 571.

  1. Orkhan Amiraslanov; Hamraz Javaheri; Sizhen Bian; Paul Lukowicz

    Preparation for Future Learning: Augmented-Reality Enhanced Interactive Physics Labs

    In: Proceedings of the International Conference on Ubiquitous Computing. International Conference on Ubiquitous Computing (Ubicomp-2018), October 8-12, Singapore, Singapore, Pages 331-334, ISBN 978-1-4503-5966-5/18/10, ACM, 2018.

  2. Nijat Mehdiyev; Joerg Evermann; Peter Fettke

    A Novel Business Process Prediction Model Using a Deep Learning Method

    In: Springer Fachmedien Wiesbaden (Hrsg.). Business & Information Systems Engineering (BISE), Vol. 5/2018, Pages 1-15, Springer Fachmedien, Wiesbaden, 7/2018.

  3. Kareem Amin; Stelios Kapetanakis; Klaus-Dieter Althoff; Andreas Dengel; Miltos Petridis

    Answering with Cases: A CBR Approach to Deep Learning

    In: Michael T. Cox; Peter Funk; Shahina Begum (Hrsg.). Case-Based Reasoning Research and Development. International Conference on Case-Based Reasoning (ICCBR-2018), July 9-12, Stockholm, Sweden, Springer, 12/2018.

  4. Ekaterina Loginova; Günter Neumann

    An Interactive Web-Interface for Visualizing the Inner Workings of the Question Answering LSTM

    In: EMNLP-2018, System Demonstration. Conference on Empirical Methods in Natural Language Processing (EMNLP-2018), November 2-4, Brüssel, Belgium, EMNLP, 11/2018.

  5. Shoaib Ahmed Siddiqui; Dominique Mercier; Mohsin Munir; Andreas Dengel; Sheraz Ahmed

    TSViz: Demystification of Deep Learning Models for Time-Series Analysis

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/1802.02952, Pages 1-13, ArXiv, 2018.

  6. Lukas Ruff; Robert Vandermeulen; Nico Goernitz; Lucas Deecke; Shoaib Ahmed Siddiqui; Alexander Binder; Emmanuel Müller; Marius Kloft

    Deep One-Class Classification

    In: International Conference on Machine Learning (ICML-2018). International Conference on Machine Learning (ICML-2018), Proceedings of Machine Learning Research, 2018.

  7. David Harbecke; Robert Schwarzenberg; Christoph Alt

    Learning Explanations From Language Data

    In: The 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP - Proceedings of the First Workshop. Analyzing and Interpreting Neural Networks for NLP (BlackboxNLP), located at EMNLP 2018, November 1, Brussels, Belgium, ISBN 978-1-948087-71-1, The Association for Computational Linguistics, 2018.

  8. Ellák Somfai; Benjámin Baffy; Kristian Fenech; Changlu Guo; Rita Hosszú; Dorina Korózs; Fabrizio Nunnari; Marcell Pólik; Daniel Sonntag; Attila Ulbert; András Lorincz

    Minimizing false negative rate in melanoma detection and providing insight into the causes of classification

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2102.09199, Pages 1-14, arXiv, 2021.

  9. Dominique Mercier; Andreas Dengel; Sheraz Ahmed

    PatchX: Explaining Deep Models by Intelligible Pattern Patches for Time-series Classification

    In: International Joint Conference on Neural Networks. International Joint Conference on Neural Networks (IJCNN-2021), July 18-22, Virtual, Vol. abs/2102.05917, Arxiv, 2021.

  10. Dominic Neu; Johannes Lahann; Peter Fettke

    A systematic literature review on state-of-the-art deep learning methods for process prediction

    In: Artificial Intelligence Review, Vol. Online, Springer Nature, 3/2021.

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