You don't need to understand every equation in a research paper to turn it into a project idea. Even experts skip details, especially in fast-moving fields like machine learning. Focus on high-level insights and what's relevant to your problem instead.
Today, so you're gonna— you will kind of practice the habits that turn a difficult paper into a clear project idea, something like that. So, uh, I'm gonna summarize what you will learn today, right? So this workshop turns a paper reading into a practical research workflow, right? You will not need to understand every equation, of course, in a famous paper to learn how research questions are built. Okay, this is a very important point I want to emphasize. Okay, even experts, they— there is no way for them to— for even experts to understand like every equation in a paper which lies in their kind of expertise actually, or lies in their kind of research, you know, area, you know. So for example, I'm, I'm doing machine learning, right? So even like specifically I'm doing, say, like a model developing, right, diffusion model, see for example, diffusion model, which is pretty hot topic today, right? Recently in this kind of machine learning community, right? Diffusion model, right? But there is no way for me to understand even like every equation, even for a single paper, there is no way for me to understand every single equation very quickly, right? So, you know, I mean, determining whether or not a research paper is gonna be useful for your own problem does not— I mean, partially depends on, you know, whether or not you understand this paper, but it does not fully depend on whether or not you fully understand this paper. So I hope you get this idea very clearly. Okay, you don't need to understand every equation in a single paper to determine whether this paper is going to be useful for you, right? So actually, you're going to do the opposite, right?
