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Improvement suggestions for the tutorial on flow matching #88
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Is it possible to include a minimal example of how a trained model can be used to evaluate the density of a given sample? |
@radiradev Thats a great idea. I can work on this. If you have an immediate need or are interested in making one I can send over a dirty notebook for this. |
@atong01 That would be very much appreciated! |
We should give credit to stochastic interpolants and rectified flows at the beginning of the notebook. Basically saying that all 3 methods are similar and concurrent ICLR2023 papers |
Hi, |
Hi, |
Hi @atong01, could you please share your example notebook on how this is done? I saw here that to evaluate the density an ode must be solved, but I am not sure how to accomplish this in pytorch: |
Hello, I cannot run the last cell in the Flow_matching_tutorial.ipynb notebook because the Thank you for the tutorials! |
Oh that’s indeed a typo… I changed the name of the function last minute and forgot to change this. You are right! The correct function is Edit: I have pushed a corrected tutorial. |
Your suggestion is fantastic, I'm a beginner and it looks like there is no difference between stochastic interpolants and rectified flows, except that stochastic interpolants have an extra random term and rectified flows seem to be a deterministic sampling, is my understanding Is my understanding correct? I look forward to your reply, thanks! |
This issue is opened for users to suggest improvements for the Flow Matching tutorial notebook.
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