Mathematically Oriented Disciplines I am a research scholar commencing my research in the field of deep learning. Deep learning uses lot of tools from mathematics. To name a few : linear algebra, probability and statistics, optimization. 

My mathematical background is very shaky. When I read research papers in deep learning, I invariably skip the sections that are mathematically heavy. However, I can understand the higher level details, such as what the research work is about, what algorithm the authors have used, and so on. But I never have the feeling of completely understanding the paper.

I feel that I cannot do original research unless I become really strong in the above mentioned subjects in mathematics. Is this claim correct?

That said, can someone publish papers in deep learning without really understanding the mathematics behind it?
I feel that I cannot do original research unless I become really strong in the above mentioned subjects in mathematics. Is this claim correct?


If it is, then what would you do about it?  Probably, take one math class per semester, and in the summer too if possible, and do some additional reading on your own when classes are not in session.

If the claim is not correct... what harm would it do to strengthen your math skills, even if they turn out not to be essential for your field?