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  2. Long short-term memory - Wikipedia

    en.wikipedia.org/wiki/Long_short-term_memory

    Long short-term memory (LSTM) [1] is a type of recurrent neural network (RNN) aimed at mitigating the vanishing gradient problem [2] commonly encountered by traditional RNNs. Its relative insensitivity to gap length is its advantage over other RNNs, hidden Markov models , and other sequence learning methods.

  3. Time aware long short-term memory - Wikipedia

    en.wikipedia.org/wiki/Time_aware_long_short-term...

    Time Aware LSTM (T-LSTM) is a long short-term memory (LSTM) unit capable of handling irregular time intervals in longitudinal patient records. T-LSTM was developed by researchers from Michigan State University, IBM Research, and Cornell University and was first presented in the Knowledge Discovery and Data Mining (KDD) conference. [1]

  4. Sepp Hochreiter - Wikipedia

    en.wikipedia.org/wiki/Sepp_Hochreiter

    Hochreiter developed the long short-term memory (LSTM) neural network architecture in his diploma thesis in 1991 leading to the main publication in 1997. [3] [4] LSTM overcomes the problem of numerical instability in training recurrent neural networks (RNNs) that prevents them from learning from long sequences (vanishing or exploding gradient).

  5. Recurrent neural network - Wikipedia

    en.wikipedia.org/wiki/Recurrent_neural_network

    That is, LSTM can learn tasks that require memories of events that happened thousands or even millions of discrete time steps earlier. Problem-specific LSTM-like topologies can be evolved. [56] LSTM works even given long delays between significant events and can handle signals that mix low and high-frequency components.

  6. Generative pre-trained transformer - Wikipedia

    en.wikipedia.org/wiki/Generative_pre-trained...

    Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.

  7. Mamba (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Mamba_(deep_learning...

    To enable handling long data sequences, Mamba incorporates the Structured State Space sequence model (S4). [2] S4 can effectively and efficiently model long dependencies by combining continuous-time, recurrent, and convolutional models. These enable it to handle irregularly sampled data, unbounded context, and remain computationally efficient ...

  8. “Laguna Beach ”Cast Reunites at 20-Year High School Reunion ...

    www.aol.com/laguna-beach-cast-reunites-20...

    Lauren Conrad/Instagram. Trey Phillips, Lauren Conrad and Dieter Schmitz at their 20th high school reunion; Laguna Beach High School’s Class of 2004 members in photos taken on Nov. 30, 2024

  9. Category:Application software templates - Wikipedia

    en.wikipedia.org/wiki/Category:Application...

    [[Category:Application software templates]] to the <includeonly> section at the bottom of that page. Otherwise, add <noinclude>[[Category:Application software templates]]</noinclude> to the end of the template code, making sure it starts on the same line as the code's last character.