Body: <p>I'm going through <a href="https://pytorch.org/docs/stable/distributions.html" rel="nofollow noreferrer">the <code>distributions</code> package</a> on PyTorch's documentation and came across the term <em>stochastic computation graph</em>. In layman's terms, what is it?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-06-20T17:55:25.437Z
Comments.Text: Hi and welcome! It may be useful if you link us to the documentation that uses that term/expression.
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-06-21T09:30:07.383Z
Comments.Text: Hi, the documentation is here: https://pytorch.org/docs/stable/distributions.html ; its detailed in https://arxiv.org/pdf/1506.05254.pdf , but I was looking for an intuitive comment on how its integrated by libraries like Tensorflow or Pytorch. Thank you!
Comments.UserDisplayName: kikram
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-06-21T11:31:55.397Z
Comments.Text: Although I haven't yet read that paper (I will try to do it so that to provide a formal answer), I think that a stochastic computation graph (SCG) is just a _computation graph_ that is able to handle stochastic or random operations, such as sampling from a normal distribution. Here, by "handle" I mean that it handles the back-propagation part of training a neural network that uses random sampling (e.g. VAEs). But, to be honest, this is just an educated guess given my experience with TensorFlow Probability and VAEs and after having read that introductory section of the documentation you linked.
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-06-21T11:48:00.313Z
Comments.Text: Just to understand how much you know about machine learning, do you know what a computation graph is? Are you familiar with variational auto-encoders or similar models that use random sampling?
Comments.UserDisplayName: nbro
Tags: <reinforcement-learning><pytorch>
Title: In layman's terms, what is stochastic computation graph?
UserDisplayName: kikram
ThreadText: # In layman's terms, what is stochastic computation graph?
  
  (Asked by: username_0 on 2020-06-20)
  
  I'm going through [the `distributions` package](https://pytorch.org/docs/stable/distributions.html) on PyTorch's documentation and came across the term *stochastic computation graph*. In layman's terms, what is it?
  
  **Tags:** reinforcement-learning, pytorch
  
  > **Comments:**
  > **username_1**: Hi and welcome! It may be useful if you link us to the documentation that uses that term/expression.  
  > **username_0**: Hi, the documentation is here: https://pytorch.org/docs/stable/distributions.html ; its detailed in https://arxiv.org/pdf/1506.05254.pdf , but I was looking for an intuitive comment on how its integrated by libraries like Tensorflow or Pytorch. Thank you!  
  > **username_1**: Although I haven't yet read that paper (I will try to do it so that to provide a formal answer), I think that a stochastic computation graph (SCG) is just a _computation graph_ that is able to handle stochastic or random operations, such as sampling from a normal distribution. Here, by "handle" I mean that it handles the back-propagation part of training a neural network that uses random sampling (e.g. VAEs). But, to be honest, this is just an educated guess given my experience with TensorFlow Probability and VAEs and after having read that introductory section of the documentation you linked.  
  > **username_1**: Just to understand how much you know about machine learning, do you know what a computation graph is? Are you familiar with variational auto-encoders or similar models that use random sampling?  
  
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  ## 0 answers
  
  