How to represent and work with the feature matrix for graph convolutional network (GCN) if the number of features for each node is different?

I have a question regarding features representation for graph convolutional neural network. For my case, all nodes have a different number of features, and for now, I don’t really understand how should I work with these constraints. I can not just reduce the number of features or add meaningless features in order to make the…

Tensorflow throwing out of bounds error with keras tokenizer

I am new to ML and tensorflow and trying to train and use a standard text generation model. When I go to train the model I get this error: Train for 155 steps Epoch 1/5 2/155 […………………………] – ETA: 4:49 – loss: 2.5786 ————————————————————————— InvalidArgumentError Traceback (most recent call last) <ipython-input-133-d70c02ff4270> in <module>() —-> 1…

Why is exp used in encoder of VAE instead of using the value of standard deviation alone?

There’s one VAE example here: https://towardsdatascience.com/teaching-a-variational-autoencoder-vae-to-draw-mnist-characters-978675c95776 And the source code of encoder: https://gist.github.com/FelixMohr/29e1d5b1f3fd1b6374dfd3b68c2cdbac#file-vae-py The author is using exp (natural exponential) for calculating values of the embedding vector: $z = Mean + Random \times e^{StandardDeviation}$ z = mn + tf.multiply(epsilon, tf.exp(sd)) It’s not related to the code (practical programming), but why using natural exponential instead of:…