Answers.Body: <p>Here's a link to my answer on <em>CV Stack Exchange</em>, where I have mentioned about latent spaces and some deep learning models that learn these representations: <a href="https://stats.stackexchange.com/questions/442352/what-is-a-latent-space/442360#442360">https://stats.stackexchange.com/questions/442352/what-is-a-latent-space/442360#442360</a></p>
  
  <p>In short, deep learning models for <a href="https://paperswithcode.com/task/domain-adaptation" rel="nofollow noreferrer">Domain Adaptation</a>, <a href="https://paperswithcode.com/area/computer-vision" rel="nofollow noreferrer">Computer Vision,</a> <a href="https://paperswithcode.com/area/natural-language-processing" rel="nofollow noreferrer">Natural Language Processing,</a> <a href="https://paperswithcode.com/task/recommendation-systems" rel="nofollow noreferrer">Recommendation Systems,</a> <a href="https://paperswithcode.com/area/music" rel="nofollow noreferrer">Music</a>/<a href="https://paperswithcode.com/area/speech" rel="nofollow noreferrer">Speech</a>/<a href="https://paperswithcode.com/area/audio" rel="nofollow noreferrer">Audio</a> processing, <a href="https://paperswithcode.com/area/adversarial" rel="nofollow noreferrer">Adversarial models</a>, etc., <strong>all</strong> learn some form of latent representation of data.</p>
  
  <p>In fact, any place we're learning a function to map input and output spaces of a dataset, the model essentially learns a latent representation of data irrespective of whether the model is based on deep neural networks or a <a href="https://en.wikipedia.org/wiki/Latent_Dirichlet_allocation" rel="nofollow noreferrer">stochastic method</a> or any other.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2019-12-30T04:28:23.123Z
Answers.LastActivityDate: 2020-01-07T04:12:03.993Z
Answers.LastEditDate: 2020-01-07T04:12:03.993Z
Answers.UserDisplayName: Balraj Ashwath
Body: <p>I know that autoencoders are one type of deep neural networks that can learn the latent representation of data. I guess there should be several other models like autoencoders. </p>
  
  <p>What are some new deep learning models for learning latent representation of data?</p>
  
Tags: <neural-networks><deep-learning><autoencoders><latent-variable>
Title: What are some new deep learning models for learning latent representation of data?
UserDisplayName: Kadaj13
ThreadText: # What are some new deep learning models for learning latent representation of data?
  
  (Asked by: username_0 on 2019-12-25)
  
  I know that autoencoders are one type of deep neural networks that can learn the latent representation of data. I guess there should be several other models like autoencoders.
  
  What are some new deep learning models for learning latent representation of data?
  
  **Tags:** neural-networks, deep-learning, autoencoders, latent-variable
  
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  ## 1 answers
  
  ### Answer by username_1 on 2019-12-30. Score: 1 | Accepted answer
  
  Here's a link to my answer on *CV Stack Exchange*, where I have mentioned about latent spaces and some deep learning models that learn these representations: <https://stats.stackexchange.com/questions/442352/what-is-a-latent-space/442360#442360>
  
  In short, deep learning models for [Domain Adaptation](https://paperswithcode.com/task/domain-adaptation), [Computer Vision,](https://paperswithcode.com/area/computer-vision) [Natural Language Processing,](https://paperswithcode.com/area/natural-language-processing) [Recommendation Systems,](https://paperswithcode.com/task/recommendation-systems) [Music](https://paperswithcode.com/area/music)/[Speech](https://paperswithcode.com/area/speech)/[Audio](https://paperswithcode.com/area/audio) processing, [Adversarial models](https://paperswithcode.com/area/adversarial), etc., **all** learn some form of latent representation of data.
  
  In fact, any place we're learning a function to map input and output spaces of a dataset, the model essentially learns a latent representation of data irrespective of whether the model is based on deep neural networks or a [stochastic method](https://en.wikipedia.org/wiki/Latent_Dirichlet_allocation) or any other.
  
  
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