I'm a programmer and I've studied some calculus and linear algebra years ago. I've been getting in to AI recently and I struggle understanding some of the mathematical notation and formulas. I apologize ahead of time if my questions are stupid.
In programming, when there exists functionality that I wish to use but do not understand, I can simply google the documentation or look at the implementation. Descriptive naming is used and it really helps with readability.
However, when it comes to mathematics, I struggle understanding how to make use of what I see in research papers. I am lost as to where I can even navigate a formula like this
$$ \\ p_{\theta}\left(\mathbf{x}_{0:T}\right) := p\left(\mathbf{x}_T\right) \prod\limits_{t=1}^T p_{\theta} \left(\mathbf{x}_{t-1} \vert \mathbf{x}_t \right), p_{\theta}\left(\mathbf{x}_{t - 1} \vert \mathbf{x}_t\right) := \mathcal{N}\left(\mathbf{x}_{t - 1} ; \mathbf{\mu}_{\theta} \left(\mathbf{x}_t, t\right), \mathbf{\Sigma}_{\theta} \left(\mathbf{x}_t, t\right)\right) \\ $$
How can I emulate the research process I use for programming?
I would like to know why they the naming they did. What do each and every symbol mean? How am I supposed to compute individual components of this formula?
Why is it
p(θ)
and not something like p(a)? Why are we using theta over another variable name? How can I better navigate my research? What resources are available to better comprehend research papers math?