Answers.Body: <p>Yes, recursive neural networks (recursive NN) are related to recurrent neural networks (RNNs), because they generalize the latter (at least, structurally), as stated in <a href="https://www.deeplearningbook.org/contents/rnn.html" rel="nofollow noreferrer">section 10.6</a> of the Deep Learning book, similar to the way that a tree generalizes a list/array.</p>
  <p>So, in a list/array, element <span class="math-container">$e_1$</span> is connected to element <span class="math-container">$e_2$</span>, which is connected to element <span class="math-container">$e_3$</span>, and so on. In a tree, element <span class="math-container">$e_1$</span> can be connected to more than one other element (node), and the same applies to the other elements, provided there are no cycles, otherwise, you get a graph, which is a generalization of a tree.</p>
  <p>If these explanations weren't yet clear, the best way to understand the difference between the two is to look at the diagrams of an RNN and a recursive NN.</p>
  <p>Here's an RNN.</p>
  <p><a href="https://i.sstatic.net/MeAOv.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/MeAOv.png" alt="enter image description here" /></a></p>
  <p>The caption should describe the diagram (in case it is not clear). The important thing to note is that, on the left, we have an RNN, which looks like a list.</p>
  <p>Here's a recursive NN.</p>
  <p><a href="https://i.sstatic.net/RGYC4.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/RGYC4.png" alt="enter image description here" /></a></p>
  <p>which looks like a tree.</p>
  <p>There are many variations of RNNs (e.g. Bidirectional RNNs, multi-layered RNNs, LSTMs, or GRUs) and recursive NNs (e.g. that attempt to have balanced trees, similar to the way that a Red-Black Tree is a balanced binary search tree), so we cannot give all the details about the differences between these two approaches.</p>
  <p>However, a few things should be kept in mind</p>
  <ul>
  <li>recursive NNs might be used in the context of parse trees</li>
  <li>recursive NNs have been used to process data structures as input to neural nets</li>
  <li>nodes in recursive NNs don't necessarily perform a linear operation followed by a non-linearity</li>
  </ul>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-12-20T14:32:01.347Z
Answers.LastActivityDate: 2021-12-20T14:39:39.833Z
Answers.LastEditDate: 2021-12-20T14:39:39.833Z
Answers.UserDisplayName: nbro
Body: <p>Recurrent neural networks, abbreviated as RNNs, are widely used in deep learning literature, especially for text processing.</p>
  <p>Are they related to recursive neural networks in any way?</p>
  <p>I am asking for the general/special relationship that enables us to view the one in terms of another if possible.</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-12-17T10:53:06.337Z
Comments.Text: The Wikipedia articles on the two types of network look like a good place for someone to start an answer.
Comments.UserDisplayName: Neil Slater
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-12-17T10:58:30.450Z
Comments.Text: @NeilSlater They seem to be different based on that, but at some places (like proofs) they are referring to the same...
Comments.UserDisplayName: hanugm
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-12-17T11:16:52.780Z
Comments.Text: Form the articles, recurrent are a sub-type of recursvive. I hope that someone who knows more about this can answer in depth.
Comments.UserDisplayName: Neil Slater
Tags: <comparison><recurrent-neural-networks>
Title: Is there any relation between the recursive neural network and recurrent neural network?
UserDisplayName: hanugm
ThreadText: # Is there any relation between the recursive neural network and recurrent neural network?
  
  (Asked by: username_0 on 2021-12-17)
  
  Recurrent neural networks, abbreviated as RNNs, are widely used in deep learning literature, especially for text processing.
  
  Are they related to recursive neural networks in any way?
  
  I am asking for the general/special relationship that enables us to view the one in terms of another if possible.
  
  **Tags:** comparison, recurrent-neural-networks
  
  > **Comments:**
  > **username_1**: The Wikipedia articles on the two types of network look like a good place for someone to start an answer.  
  > **username_0**: @username_1 They seem to be different based on that, but at some places (like proofs) they are referring to the same...  
  > **username_1**: Form the articles, recurrent are a sub-type of recursvive. I hope that someone who knows more about this can answer in depth.  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_2 on 2021-12-20. Score: 0
  
  Yes, recursive neural networks (recursive NN) are related to recurrent neural networks (RNNs), because they generalize the latter (at least, structurally), as stated in [section 10.6](https://www.deeplearningbook.org/contents/rnn.html) of the Deep Learning book, similar to the way that a tree generalizes a list/array.
  
  So, in a list/array, element $e\_1$ is connected to element $e\_2$, which is connected to element $e\_3$, and so on. In a tree, element $e\_1$ can be connected to more than one other element (node), and the same applies to the other elements, provided there are no cycles, otherwise, you get a graph, which is a generalization of a tree.
  
  If these explanations weren't yet clear, the best way to understand the difference between the two is to look at the diagrams of an RNN and a recursive NN.
  
  Here's an RNN.
  
  [![enter image description here](https://i.sstatic.net/MeAOv.png)](https://i.sstatic.net/MeAOv.png)
  
  The caption should describe the diagram (in case it is not clear). The important thing to note is that, on the left, we have an RNN, which looks like a list.
  
  Here's a recursive NN.
  
  [![enter image description here](https://i.sstatic.net/RGYC4.png)](https://i.sstatic.net/RGYC4.png)
  
  which looks like a tree.
  
  There are many variations of RNNs (e.g. Bidirectional RNNs, multi-layered RNNs, LSTMs, or GRUs) and recursive NNs (e.g. that attempt to have balanced trees, similar to the way that a Red-Black Tree is a balanced binary search tree), so we cannot give all the details about the differences between these two approaches.
  
  However, a few things should be kept in mind
  
  * recursive NNs might be used in the context of parse trees
  * recursive NNs have been used to process data structures as input to neural nets
  * nodes in recursive NNs don't necessarily perform a linear operation followed by a non-linearity
  
  
  ---
  
  