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Showing 1 to 3 of 3 for “"Deep Recurrent Neural Networks"”.

  1. Predicting Disease Progression Using Deep Recurrent Neural Networks and Longitudinal Electronic Health Record Data

    … there have been attempts to utilize temporal neural network models to predict clinical intervention time and mortality in the intensive care unit (ICU) and recurrent neural network (RNN) models to predict multiple types of medical conditions as well as medication use. However, such work has …

    wustl Repository record for Predicting Disease Progression Using Deep Recurrent Neural Networks and Longitudinal Electronic Health Record Data (opens in a new tab)

  2. Astrometric and Photometric Data Fusion in Machine Learning-Based Characterization of Resident Space Objects

    … data en masse on near-geosynchronous RSOs; and a deep machine learning approach to orbital regime identification of cislunar RSOs from telescope observational data. These topics represent significant advancement in the field of SSA in three different areas associated with the RSO characterization …

    arizona-thes Repository record for Astrometric and Photometric Data Fusion in Machine Learning-Based Characterization of Resident Space Objects (opens in a new tab)

  3. Deep Recurrent Q Networks for Dynamic Spectrum Access in Dynamic Heterogeneous Envirnments with Partial Observations

    … scenarios. Thus, the combination of sensing with deep reinforcement learning (DRL) has been shown to be a promising alternative to previously proposed simplistic approaches. DRL does not require the explicit estimation of transition probability matrices and prohibitively large matrix computations …

    vt Repository record for Deep Recurrent Q Networks for Dynamic Spectrum Access in Dynamic Heterogeneous Envirnments with Partial Observations (opens in a new tab)