red-sd
DeepExplicitDurationSwitchingModels forTimeSeries
Time series forecasting plays akeyrole in informing industrial and business decisions [17,24,8], while segmentation isuseful forunderstanding biological andphysicalsystems [40,45,34].
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- Information Technology > Artificial Intelligence > Representation & Reasoning (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning (0.68)
- Information Technology > Artificial Intelligence > Machine Learning > Learning Graphical Models > Directed Networks > Bayesian Learning (0.68)
Deep Explicit Duration Switching Models for Time Series
We propose the Recurrent Explicit Duration Switching Dynamical System (RED-SDS), a flexible model that is capable of identifying both state-and time-dependent switching dynamics.
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- Asia > Singapore (0.04)
- North America > United States > Massachusetts > Norfolk County > Norwood (0.04)
- North America > United States > California > San Francisco County > San Francisco (0.04)
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Technology:
Deep Explicit Duration Switching Models for Time Series
We propose the Recurrent Explicit Duration Switching Dynamical System (RED-SDS), a flexible model that is capable of identifying both state-and time-dependent switching dynamics.
Country:
- Asia > Singapore (0.04)
- North America > United States > Massachusetts > Norfolk County > Norwood (0.04)
- Europe > United Kingdom > England > Oxfordshire > Oxford (0.04)
- (2 more...)
Technology:
- Information Technology > Artificial Intelligence > Representation & Reasoning (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning (0.68)
- Information Technology > Artificial Intelligence > Machine Learning > Learning Graphical Models > Directed Networks > Bayesian Learning (0.68)