I wrote a blog post! In an ML paper reading group awhile back, we were going through a paper on flow models and I realized I didn't really understand the change-of-variables formula in probability as well as I should. So I wrote up this post and put together some interactive visuals to help me more fully understand my main point of confusion (how/why the Jacobian inverse term plays into the formula).
I'm sharing my writeup here in the hope that folks will find the visualizations as useful as I did. I hope you enjoy reading, and I'm always grateful for feedback on the prose or visuals if you have any!
