I have some minor complaints but overall I think this is great! My background is in physics, and I remember finally understanding every equation on the formula sheet given to us for exams... that really felt like I finally understood a lot of physics. There's great value in being comprehensive so that a learner can choose themselves to dive deeper, and for those with more experience to check their own knowledge.

Having said that, let me raise some objections:

1. Omitting the multi-layer perceptron is a major oversight. We have backpropagation here, but not forward propagation, so to speak.

2. Omitting kernel machines is a moderate oversight. I know they're not "hot" anymore but they are very mathematically important to the field.

3. The equation for forward diffusion is really boring... it's not that important that you can take structured data and add noise incrementally until it's all noise. What's important is that in some sense you can (conditionally) reverse it. In other words, you should put the reverse diffusion equation which of course is considerably more sophisticated.