Answers.Body: <p>Usually in CNF you want to learn a vector field network <span class="math-container">$\mathcal{v^t(x)}$</span>, which with some abuse of notation, can be red as <span class="math-container">$\mathcal{v(x|t)}$</span>, so wither you create a network for each time (pretty expensive), or you hope that a network can learn the time-conditional vector field, thus you feed the net the time, so that it knows which vector field you want</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2024-08-15T13:54:22.990Z
Answers.LastActivityDate: 2024-08-15T13:54:22.990Z
Answers.UserDisplayName: Alberto
Body: <p>I was going through the flow matching paper by Lipmann and others. I understood the paper fairly well. I was also looking at the code for the same over <a href="https://github.com/jmtomczak/intro_dgm/blob/main/sbgms/fm_example.ipynb" rel="nofollow noreferrer">here</a>. One thing I did not understand in the code is the computation of a time embedding to compute the velocity field. Why is it necessary to incorporate a time embedding?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-08-14T19:13:41.533Z
Comments.Text: you want xt=xt-1+f(xt-1), thus you need to tell the net the “t” term
Comments.UserDisplayName: Alberto
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-08-15T12:54:57.607Z
Comments.Text: Thank you, this clears it up for me. I missed this for some reason. You can type this up as the answer, and I will be happy to mark it as accepted.
Comments.UserDisplayName: pseudomonas
Tags: <neural-networks><generative-model>
Title: Role of time embedding in flow matching
UserDisplayName: pseudomonas
ThreadText: # Role of time embedding in flow matching
  
  (Asked by: username_0 on 2024-08-14)
  
  I was going through the flow matching paper by Lipmann and others. I understood the paper fairly well. I was also looking at the code for the same over [here](https://github.com/jmtomczak/intro_dgm/blob/main/sbgms/fm_example.ipynb). One thing I did not understand in the code is the computation of a time embedding to compute the velocity field. Why is it necessary to incorporate a time embedding?
  
  **Tags:** neural-networks, generative-model
  
  > **Comments:**
  > **username_1**: you want xt=xt-1+f(xt-1), thus you need to tell the net the “t” term  
  > **username_0**: Thank you, this clears it up for me. I missed this for some reason. You can type this up as the answer, and I will be happy to mark it as accepted.  
  
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  ## 1 answers
  
  ### Answer by username_1 on 2024-08-15. Score: 2 | Accepted answer
  
  Usually in CNF you want to learn a vector field network $\mathcal{v^t(x)}$, which with some abuse of notation, can be red as $\mathcal{v(x|t)}$, so wither you create a network for each time (pretty expensive), or you hope that a network can learn the time-conditional vector field, thus you feed the net the time, so that it knows which vector field you want
  
  
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