Sentence examples for sequence models from inspiring English sources

Deep Sequence Models: Context Representation, Regularization, and Application to Language.

- Effectively combining supervised learning and RL to train generative sequence models.

Her work at Columbia is about combining probabilistic graphical modeling and deep learning to design better sequence models.

From a more practical aspect, the present results highlight an essential role of long-range effects in precisely defining protein families, which are absent in conventional sequence models.

Having said that, the existing sequence models also have a lot in common, with the main difference being in the style of conceptual packaging of the same succession of strata (i.e., where to pick the sequence boundaries).

Methods of word segmentation vary from having a large vocabulary and taking the longest vocabulary match with some heuristics for unknown words to the use of machine learning sequence models, such as hidden Markov models or conditional random fields, trained over hand-segmented words (see the references in Section 2.5 ).

Bird Species Recognition Combining Acoustic and Sequence Modeling.

Zhou, J. & Troyanskaya, O. G. Predicting effects of noncoding variants with deep-learning-based sequence model.

Zhou, J. & Troyanskaya, O.G. Predicting effects of noncoding variants with deep learning-based sequence model.

A sequence model, such as an HMM or LSTM, guidesthe search for good paths.

Predicting effects of noncoding variants with deep learningâ€basedd sequence model.