jakiwjakiw
jakiwjakiw OP t1_ir960po wrote
Reply to comment by Serverside in [R] Introduction to Diffusion Models in JAX by jakiwjakiw
That's great to hear, please keep me posted on your progress!
jakiwjakiw OP t1_ir6m6wg wrote
Reply to comment by Serverside in [R] Introduction to Diffusion Models in JAX by jakiwjakiw
That's a pretty interesting question! Actually, I don't know. As far as I know there are currently multiple ways to do conditional generation with SGMs, depending on what your requirements are. I like the work https://arxiv.org/abs/2111.13606 on that regard. But it's also something I wanted to explore in a bit more depth.
Very happy about any input about this!
jakiwjakiw OP t1_ir6lny2 wrote
Reply to comment by Small_Stand_8716 in [R] Introduction to Diffusion Models in JAX by jakiwjakiw
I mainly used flax since most of the code I was reading myself was also using flax, but I wouldn't be able to objectively compare them since I haven't used haiku yet. So can't help, sorry!
jakiwjakiw OP t1_ir6k6b9 wrote
Reply to comment by velcher in [R] Introduction to Diffusion Models in JAX by jakiwjakiw
The delta's stand are point measures. \delta_x has mass 1 at the point x and 0 everywhere else.
Therefore \hat\mu is the measure that has mass 1/J at each x_j and 0 everywhere else.
These point measures are also called "dirac delta" and the notation using the delta is common in my field, but it is rather confusing to just use them like that without explanation, thanks a lot for pointing that out. Will update that!
Submitted by jakiwjakiw t3_xwam5y in MachineLearning
jakiwjakiw OP t1_ir9d2b4 wrote
Reply to comment by Sea_Discussion_459 in [R] Introduction to Diffusion Models in JAX by jakiwjakiw
Thanks! Didn't notice that. You can find it here:
https://jakiw.com/SGM%20Introduction.ipynb
I've updated the link on the website too :)