# Tagged Questions

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### How to split data for LSTM prediction of a vector?

I'm trying to decide how to best split my data to train a LSTM to predict the next time series vector, currently my inputs are 255,30 . So 255 time steps with each containing a vector of length 30 ...
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### Are all generative Models based on Bayes?

Reading about deep learning I encounter various different kinds of hierarchical networks, many of which are generative. 1) Are all of the generative networks based on Bayes? 2) If not, how do they ...
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### Question regarding Gaussian Discriminant Analysis, and Generative Learning models

In lecture today, my professor mentioned in the context of GDA and Generative learning, we would like to learn the joint probability $P(x, y)$, where $x \in \mathbb{R}^n$ and $y \in \{+1, -1\}$. ...
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### How does the reparameterization trick for VAEs work and why is it important?

How does the reparameterization trick for variational autoencoders (VAE) work? Is there an intuitive and easy explanation without simplifying the underlying math? And why do we need the 'trick'?
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### Prediction without labelled data

I am working on a churn prediction model, where I am trying to predict probability of employee churn. For each employee I have the following features 1) Role 2) Total experience 3) Current experience ...
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### What is the relationship between generative models and density estimation?

If aren't they synonymous, what distinguishes the one from the other? Is probability density estimation a certain kind of generative model? Can any generative model be regarded as density estimation?
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### Generative vs. discriminative

I know that generative means "based on $P(x,y)$" and discriminative means "based on $P(y|x)$," but I'm confused on several points: Wikipedia (+ many other hits on the web) classify things like SVMs ...