Shared Models and Custom Losses in Tensorflow 2 / Keras

By Medium - 2020-12-15

Description

Developing an advanced neural network model in Tensorflow 2 and Keras

Summary

The decoder φ-inverse, which reconstructs the input from the latent code The linear dynamics K, which describe how the latent code evolves over time Keras Refresher To start building the model, we can define the three sub-models as follows: To share models, we first define the encoder, decoder, and linear dynamics models.
x1 vs x1_pred linearity of dynamics: With DeepKoopman, we know the target values for losses (1) and (2), but y1 and y1_pred do not have ground truth values, so we cannot use the same approach to calculate loss (3).

Topics

Machine_Learning (0.19)
NLP (0.11)
Frontend (0.01)

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