Hi Kamer!



 Kamer_Ali_Yuksel:

I would like a NN to learn how to sample from a complex distribution in high-dimensions (e.g. 10-100K dimensions).


I don’t think that neural networks are a natural approach for sampling
from high-dimensional distributions – not that I know what your
specific use case is.
Your distribution is described by a probability-destiny function that is
a function of the 10-100K coordinates of your high-dimensional space.
Can you compute reasonably efficiently the changes in the PDF as
you take “simple” steps that move you about in that space?
If so, the “standard” approach for sampling from such a distribution
is a Markov-chain Monte Carlo.
Best.
K. Frank