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Publikationen

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  1. 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.

  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. Mohsin Munir; Muhammad Ali Chattha; Sheraz Ahmed; Andreas Dengel

    A Comparative Analysis of Traditional and Deep Learning-based Anomaly Detection Methods for Streaming Data

    In: 18th IEEE International Conference on Machine Learning and Applications. International Conference on Machine Learning and Applications (ICMLA-2019), December 16-19, Boca Raton, Florida, USA, Pages 561-566, ISBN 978-1-7281-4550-1, IEEE, 12/2019.

  4. Muhammad Ali Chatta; Muhammad Shoaib Ahmed Siddiqui; Moshin Munir; Ludger van Elst; Imran Malik; Andreas Dengel; Sheraz Ahmed

    DeepEX: Bridging the Gap Between Knowledge and Data Driven Techniques for Time Series Forecasting

    In: The 28th International Conference on Artificial Neural Networks. International Conference on Artificial Neural Networks (ICANN-2019), September 17-19, Munich, Germany, IEEE, 9/2019.

  5. Mohsin Munir; Shoaib Ahmed Siddiqui; Muhammad Ali Chattha; Andreas Dengel; Sheraz Ahmed

    FuseAD: Unsupervised Anomaly Detection in Streaming Sensors Data by Fusing Statistical and Deep Learning Models

    In: Sensors - Open Access Journal (Sensors), Vol. 19, No. 11, Pages 1-15, MDPI, 5/2019.

  6. Muhammad Ali Chattha; Shoaib Ahmed Siddiqui; Muhammad Imran Malik; Ludger van Elst; Andreas Dengel; Sheraz Ahmed

    KINN: Incorporating Expert Knowledge in Neural Networks

    In: AAAI-MAKE. AAAI Spring Symposium (AAAI SSS-2019), March 25-27, Stanford, CA, USA, AAAI, 3/2019.