# Questions tagged [variational-inference]

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### Understanding the Evidence Lower Bound (ELBO)

I am reading this tutorial about Variational Inference, which includes the following depiction of ELBO as the lower bound on log-likelihood on the third page. In the tutorial, $x_i$ is the observed ...
17 views

### mean-field variational inference in Nonconjugate Models

I'm trying to conduct mean-field Variational Inference (VI) with Nonconjugate model. I found Variational Inference in ...
17 views

### Modifying Variational Inference to be robust to outliers?

Normally, for variational inference, you have some evidence data $Z$, you have some true distribution $P(X|Z)$, and you have a simpler parameterized distribution $Q(X|\theta)$, and you're trying to ...
1 vote
54 views

### VAE: what activation function (if any) to use for the last layer of my decoder if I don't want to assume any knowledge about the scale of my inputs?

I'm working on an implementation of a Variational Autoencoder (VAE). There are lots of helpful examples and guides out there, which typically introduce VAE in the context of image data, e.g. MNIST. ...
1 vote
23 views

### Why do we use the same parameters for the joint, marginal and conditional distributions in VAEs?

I've noticed in several resources on variational autoencoders (for example the Wikipedia article), we use the same parameters theta ($\theta$) for the prior, likelihood, posterior, etc distributions. ...
78 views

### Why Reparameterization Trick does not work with discrete latent variables?

I came to know from the Youtube Video here (Timestamp 1:03:55) that Reparameterization trick only works for continuous latent variable. But, I am not clear as to why it does not work for discrete ...
57 views

### Prior in variational autoencoders

I am currently dealing with variational autoencoders where I've read the original paper "An introduction to variational Bayes" from Kingma and Welling. I am currently still a little confused ...
15 views

### Variational Inference Mean-Field Gaussian

I am new to variational inference and got very confused about some basic ideas. We want to use the mean-field gaussian family to approximate a complicated high-dimensional distribution. I want to ...
19 views

9 views

### Constraining reconstructed vectors to lie in a hyperplane ina VAE

I'm trying to add a linear constraint to my variational autoencoder model. Let's say that my input is made of two concatenated vectors: $\textbf{x} = \textbf{t} \oplus \textbf{y}$ where (for example) ...
1 vote
46 views

### Using a Variational AutoEncoder with an inverse bottleneck

For a problem I'm dealing with, I'm trying to understand if my approach could make sense. I'm using a Variational AutoEncoder (VAE) having relatively low-dimensional inputs, say $x \in \mathbb{R}^n$. ...
93 views

### Higher latent space than Input space in a Variational autoencoder (VAE)

Could it make any sense to choose a larger dimension for the latent space of the VAE with respect to the original input? For example, we may want to learn how to reconstruct a relatively low-...
37 views

### Why is KL divergence used as a measure of closeness in variational inference?

I am curious why KL divergence is the standard measure of (dis)similarity used in VI while it is not even a proper metric (asymmetric and does not satisfy triangle inequality).
26 views