Some of the variables, some of the parameters, some of the times, with some physics known: Identification with partial information

no code implementations • 27 Apr 2023 • Saurabh Malani, Tom S. Bertalan, Tianqi Cui, Jose L. Avalos, Michael Betenbaugh, Ioannis G. Kevrekidis

Iterates of such neural-network models allow for learning from data sampled at arbitrary time points $\textit{without}$ data modification.

Imputation Numerical Integration

Initializing LSTM internal states via manifold learning

no code implementations • 27 Apr 2021 • Felix P. Kemeth, Tom Bertalan, Nikolaos Evangelou, Tianqi Cui, Saurabh Malani, Ioannis G. Kevrekidis

We present an approach, based on learning an intrinsic data manifold, for the initialization of the internal state values of LSTM recurrent neural networks, ensuring consistency with the initial observed input data.

Time Series Time Series Analysis