Markov Chain Neural Networks
Awiszus, Maren, Rosenhahn, Bodo
In this work we present a modified neural network model which is capable to simulate Markov Chains. We show how to express and train such a network, how to ensure given statistical properties reflected in the training data and we demonstrate several applications where the network produces non-deterministic outcomes. One example is a random walker model, e.g.
May-2-2018
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