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Activity Number: 12 - High-Dimensional Parameter Learning on Spatio-Temporal Hidden Markov Models and Its Applications in Epidemiology
Type: Invited
Date/Time: Sunday, August 8, 2021 : 1:30 PM to 3:20 PM
Sponsor: IMS
Abstract #316905
Title: Partially Observed Time Series Models Using Long Short-Term Memory Models
Author(s): Yves Atchade*
Companies: Boston University
Keywords: Times Series; Partially observed time series; LSTM

Long short-term memory (LSTM) models are commonly used in machine learning to deal with time series data. The use of these models with partially observed time series data has not been widely explored. This talk describes a minimum distance estimation procedure for fitting LSTM models with partially observed time series data.

Authors who are presenting talks have a * after their name.

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