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Publications

Displaying results 1771 to 1780 of 13814.

  1. Nicolò Parmiggiani; Andrea Bulgarelli; Alessandro Ursi; Antonio Macaluso; Ambra Di Piano; Valentina Fioretti; Alessio Aboudan; Leonardo Baroncelli; Antonio Addis; Marco Tavani; Carlotta Pittori

    A Deep-learning Anomaly-detection Method to Identify Gamma-Ray Bursts in the Ratemeters of the AGILE Anticoincidence System

    In: The Astrophysical Journal (ApJ), Vol. 945, No. 2, Pages 1-12, IOP, 3/2023.

  2. Muhammad Ali Chattha; Muhammad Imran Malik; Andreas Dengel; Sheraz Ahmed

    Knowledge Forcing: Fusing Knowledge-Driven Approaches with LSTM for Time Series Forecasting

    In: Springer (Hrsg.). Knowledge Forcing: Fusing Knowledge-Driven Approaches with LSTM for Time Series Forecasting. International Conference on Artificial Neural Networks (ICANN), September 26-30, Crete, Greece, Vol. 14259, Springer, 2023.

  3. Muhammad Ali Chattha; Ludger van Elst; Muhammad Imran Malik; Andreas Dengel; Sheraz Ahmed

    DeepLSF: Fusing Knowledge and Data for Time Series Forecasting

    In: IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Vol. NA, Page NA, IEEE, 2023.

  4. Jan Ehrhardt; Heinz Handels

    Implicitly Solved Regularization for Learning-Based Image Registration

    In: Xiaohuan Cao; Xuanang Xu; Islem Rekik; Zhiming Cui; Xi Ouyang (Hrsg.). Machine Learning in Medical Imaging. International Workshop on Machine Learning in Medical Imaging (MLMI-2023), located at International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023), October 8, Vancouver, Canada, Pages 137-146, Lecture Notes in Computer Science (LNCS), Vol. 14348, ISBN 978-3-031-45673-2, Springer Nature Switzerland, 2024.

  5. Luc De Raedt; Angelika Kimmig; Bernd Gutmann; Kristian Kersting; Vítor Santos Costa; Hannu Toivonen

    Probabilistic Inductive Querying Using ProbLog

    In: Saso Dzeroski; Bart Goethals; Pance Panov (Hrsg.). Inductive Databases and Constraint-Based Data Mining. Pages 229-262, Springer, 2010.

  6. Kristian Kersting; Mirwaes Wahabzada; Christian Thurau; Christian Bauckhage

    Hierarchical Convex NMF for Clustering Massive Data

    In: Masashi Sugiyama; Qiang Yang (Hrsg.). Proceedings of the 2nd Asian Conference on Machine Learning. Asian Conference on Machine Learning (ACML-2010), November 8-10, Tokyo, Japan, Pages 253-268, JMLR Proceedings, Vol. 13, JMLR.org, 2010.

  7. Zhao Xu; Kristian Kersting; Thorsten Joachims

    Fast Active Exploration for Link-Based Preference Learning Using Gaussian Processes

    In: José L. Balcázar; Francesco Bonchi; Aristides Gionis; Michèle Sebag (Hrsg.). Machine Learning and Knowledge Discovery in Databases, European Conference. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD-2010), September 20-24, Barcelona, Spain, Pages 499-514, Lecture Notes in Computer Science, Vol. 6323, Springer, 2010.

  8. Tobias Lang; Marc Toussaint; Kristian Kersting

    Exploration in Relational Worlds

    In: José L. Balcázar; Francesco Bonchi; Aristides Gionis; Michèle Sebag (Hrsg.). Machine Learning and Knowledge Discovery in Databases, European Conference. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD-2010), September 20-24, Barcelona, Spain, Pages 178-194, Lecture Notes in Computer Science, Vol. 6322, Springer, 2010.

  9. Benjamin Hättasch; Carsten Binnig

    Know Better - A Clickbait Resolving Challenge

    In: Nicoletta Calzolari; Frédéric Béchet; Philippe Blache; Khalid Choukri; Christopher Cieri; Thierry Declerck; Sara Goggi; Hitoshi Isahara; Bente Maegaard; Joseph Mariani; Hélène Mazo; Jan Odijk; Stelios Piperidis (Hrsg.). Proceedings of the Thirteenth Language Resources and Evaluation Conference. International Conference on Language Resources and Evaluation (LREC-2022), June 20-25, Marseille, France, Pages 515-523, European Language Resources Association, 2022.

  10. Pratyush Agnihotri; Boris Koldehofe; Carsten Binnig; Manisha Luthra

    PANDA: performance prediction for parallel and dynamic stream processing

    In: Yongluan Zhou; Panos K. Chrysanthis; Vincenzo Gulisano; Eleni Tzirita Zacharatou (Hrsg.). 16th ACM International Conference on Distributed and Event-based Systems. ACM International Conference on Distributed and Event-Based Systems (DEBS-2022), June 27-30, Copenhagen, Denmark, Pages 180-181, ACM, 2022.

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