TensorFlow Chaotic Prediction and Blow Up
M. Andrecut
Predicting the dynamics of chaotic systems is one of the most challenging
tasks for neural networks, and machine learning in general. Here we aim to
predict the spatiotemporal chaotic dynamics of a high-dimensional non-linear
system. In our attempt we use the TensorFlow library, representing the state of
the art for deep neural networks training and prediction. While our results are
encouraging, and show that the dynamics of the considered system can be
predicted for short time, we also indirectly discovered an unexpected and
undesirable behavior of the TensorFlow library. More specifically, the longer
term prediction of the system's chaotic behavior quickly deteriorates and blows
up due to the nondeterministic behavior of the TensorFlow library. Here we
provide numerical evidence of the short time prediction ability, and of the
longer term predictability blow up.