Is there academic research on how to choose the number of layers and neurons in a neural network? I did some research and I understand that there is no right answer in choosing the number of layers and neurons in a neural network architecture. I have seen some guidelines and rules of thumb in posts and blogs. Even though they are helpful, I am wondering if there is any academic paper on them.
Do you have any study/work/research about how to choose the number of layers and neurons to share?

The research field investigating this is called Neural Architecture Search. A recent very detailed review could be a great guide :
Automated Deep Learning: Neural Architecture Search Is Not the End.
Xuanyi Dong, David Jacob Kedziora, Katarzyna Musial, Bogdan Gabrys.
arXiv:2112.09245 (2021)
