Skip to main content Skip to main navigation

Publications

Search narrowed by:

Year: 2020
Remove all filters
Displaying results 51 to 60 of 70.

  1. Peter Hevesi; Ramprasad Chinnaswamy Devaraj; Matthias Tschöpe; Oliver Petter; Janis Nikolaus Elfert; Vitor Fortes Rey; Marco Hirsch; Paul Lukowicz

    Towards Construction Progress Estimation Based on Images Captured on Site

    In: EAI IndustrialIoT 2020 - 4th EAI International Conference on Industrial IoT Technologies and Applications. EAI International Conference on …

  2. Lauren Michelle Pfeifer; Matias Valdenegro-Toro

    Automatic Detection and Classification of Tick-borne Skin Lesions using Deep Learning

    In: Workshop: LXAI Research @ NeurIPS 2020. LatinX in AI Research Workshop (LXAI-2020), located at NeurIPS2020, December 7, Virtual, Keine, 2020.

  3. Matthias Rosynski; Frank Kirchner; Matias Valdenegro-Toro

    Are Gradient-based Saliency Maps Useful in Deep Reinforcement Learning?

    In: ICBINB@NeurIPS 2020 - Bridging the gap between theory and empiricism in probabilistic machine learning. I Can't Believe It's Not Better! Workshop …

  4. Nijat Mehdiyev

    Explainable Process Predictions (xPP): A Holistic Framework and Applications

    In: Claudio Di Ciccio; Benoît Depaire; Jochen De Weerdt; Chiara Di Francescomarino; Jorge Munoz-Gama (Hrsg.). ICPM 2020. International Conference on …

  5. Marcel Heinz; Jakob Michael Schönborn; Klaus-Dieter Althoff

    Development and Implementation of a Case-Based Reasoning Approach to Speed-Up Deep Reinforcement Learning through Case-Injection for AI Gameplay

    In: Daniel Trabold; Pascal Welke; Nico Piatkowski (Hrsg.). Lernen, Wissen, Daten, Analysen. GI-Workshop-Tage "Lernen, Wissen, Daten, Analysen" …

  6. Nijat Mehdiyev; Peter Fettke

    Prescriptive process analytics with deep learning and explainable artificial intelligence

    In: Twenty-Eighth European Conference on Information Systems (ECIS2020) - A Virtual AIS Conference. European Conference on Information Systems …

  7. Benjamin Hilprecht; Carsten Binnig; Uwe Röhm

    Learning a Partitioning Advisor for Cloud Databases

    In: David Maier; Rachel Pottinger; AnHai Doan; Wang-Chiew Tan; Abdussalam Alawini; Hung Q. Ngo (Hrsg.). Proceedings of the 2020 International …

  8. Benjamin Hilprecht; Carsten Binnig; Tiemo Bang; Muhammad El-Hindi; Benjamin Hättasch; Aditya Khanna; Robin Rehrmann; Uwe Röhm; Andreas Schmidt; Lasse Thostrup; Tobias Ziegler

    DBMS Fitting: Why should we learn what we already know?

    In: 10th Conference on Innovative Data Systems Research. Conference on Innovative Data Systems Research (CIDR-2020), January 12-15, Amsterdam, …

  9. Benjamin Hilprecht; Andreas Schmidt; Moritz Kulessa; Alejandro Molina; Kristian Kersting; Carsten Binnig

    DeepDB: Learn from Data, not from Queries!

    In: Proceedings of the VLDB Endowment (PVLDB), Vol. 13, No. 7, Pages 992-1005, Association for Computing Machinery (ACM), 2020.

  10. Nathaniel Weir; Prasetya Utama; Alex Galakatos; Andrew Crotty; Amir Ilkhechi; Shekar Ramaswamy; Rohin Bhushan; Nadja Geisler; Benjamin Hättasch; Steffen Eger; Ugur Çetintemel; Carsten Binnig

    DBPal: A Fully Pluggable NL2SQL Training Pipeline

    In: David Maier; Rachel Pottinger; AnHai Doan; Wang-Chiew Tan; Abdussalam Alawini; Hung Q. Ngo (Hrsg.). Proceedings of the 2020 International …

Year