Skip to main content Skip to main navigation

Publikationen

 

Aufgrund von Wartungsarbeiten ist die Suche von Publikationen nach Autor:innen derzeit nicht möglich.

Zeige Ergebnisse 81 bis 90 von 599
  1. Daniel Thewes; Emil V. Stanev; Oliver Zielinski

    Sensitivity of a 3D Shelf Sea Ecosystem Model to Parameterizations of the Underwater Light Field

    In: Frontiers in Marine Science (FMarS), Vol. 6, No. 816, Pages 1-15, Lausanne, Schweiz, 1/2020.

  2. Jochen Wollschläger; Beke Tietjen; Daniela Voß; Oliver Zielinski

    An Empirically Derived Trimodal Parameterization of Underwater Light in Complex Coastal Waters – A Case Study in the North Sea

    In: Frontiers in Marine Science (FMarS), Vol. 7, No. 512, Pages 1-16, Frontiers Media SA, Lausanne, 6/2020.

  3. Frederic Theodor Stahl; Etienne Roesch; Timothée Dubuc

    Mapping the Big Data Landscape: Technologies, Platforms and Paradigms for Real-Time Analytics of Data Streams

    In: IEEE Access, Vol. 9, No. 24, Pages 15351-15374, IEEE Xplore, Piscataway, New Jersey, 2020.

  4. Deep Down the Rabbit Hole: On References in Networks of Decoy Elements

    In: 2020 International Conference on Cyber Security and Protection of Digital Services (Cyber Security). International Conference on Cyber Security …

  5. 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.

  6. Akshatha Kamath; Dwaraknath Gnaneshwar; Matias Valdenegro-Toro

    Know Where To Drop Your Weights: Towards Faster Uncertainty Estimation

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

  7. 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 …

  8. Luis Octavio Arriaga Camargo; Matias Valdenegro-Toro

    Unsupervised Difficulty Estimation with Action Scores

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

  9. Oliver Amft; Luis Ignacio Lopera; Paul Lukowicz; Sizhen Bian; Paul Burggraf

    Wearables to Fight COVID-19: From Symptom Tracking to Contact Tracing

    In: IEEE Pervasive Computing, Vol. 19, Pages 53-60, IEEE, 12/2020.

  10. Simon Duque Antón; Daniel Fraunholz; Daniel Schneider

    Investigating the Ecosystem of Offensive Information Security Tools

    In: Hans Dieter Schotten; Bin Han (Hrsg.). Proceedings of the 1st Workshop on Next Generation Networks and Applications. Workshop on Next Generation …