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Publications

Displaying results 231 to 240 of 578.

  1. 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.

  2. 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.

  3. 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.

  4. Andrea Galassi; Kristian Kersting; Marco Lippi; Xiaoting Shao; Paolo Torroni

    Neural-Symbolic Argumentation Mining: An Argument in Favor of Deep Learning and Reasoning

    In: Frontiers in Big Data, Vol. 2 - 2019, Pages 0-10, Frontiers, 1/2020.

  5. Jason Raphael Rambach; Bruno Mirbach; Yuriy Anisimov; Didier Stricker

    Time-of-Flight Depth Sensing for Automotive Safety and Smart Building Applications: The VIZTA Project

    In: IEEE Access (IEEE), Vol. 11, Pages 105819-105829, IEEE, 10/2023.

  6. David Steinmann; Wolfgang Stammer; Felix Friedrich; Kristian Kersting

    Learning to Intervene on Concept Bottlenecks

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2308.13453, Pages 0-10, arXiv, 2023.

  7. Michael Lutter; Christian Ritter; Jan Peters

    Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning

    In: 7th International Conference on Learning Representations. International Conference on Learning Representations (ICLR-2019), May 6-9, New Orleans, LA, USA, OpenReview.net, 2019.

  8. Summra Saleem; Muhammad Nabeel Asim; Ludger van Elst; Andreas Dengel

    FNReq-Net: A hybrid computational framework for functional and non-functional requirements classification

    In: Journal of King Saud University - Computer and Information Sciences, Vol. 35, No. 8 (101665), Elsevier, 9/2023.

  9. Saifullah Saifullah; Stefan Agne; Andreas Dengel; Sheraz Ahmed

    Analyzing the potential of active learning for document image classification

    In: International Journal on Document Analysis and Recognition (IJDAR), Vol. 26, Pages 187-209, Springer Nature, 4/2023.

  10. Mehran Jeelani; Sadbhawna; Noshaba Cheema; Klaus Illgner-Fehns; Philipp Slusallek; Sunil Jaiswal

    Expanding Synthetic Real-World Degradations for Blind Video Super Resolution

    In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. New Trends in Image Restoration and Enhancement Workshop (NTIRE-2023), 8th, located at CVPR-2023, June 18, Vancouver, BC, Canada, Pages 1199-1208, Conference on Computer Vision and Pattern Recognition (CVPR) Workshops (CVPRW), IEEE Xplore, 6/2023.

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