Hi guys. I’m really super beginer for Learning.
I took a basic course in FAST AI for 2 weeks.
Now I major in physics and about to write a paper.
My objective is that Predict a Image with dataset(which is numeric value)
I have dataset which is atomic coordinate(ex. x : 0.5, y : 0.3, z : 0.7…), lattice parameter ( a : 0.2 , b : 0.6 …) and each dataset has a graph(Image) that corresponds to dataset.
My Idea is … ** Assumed the graph image is 20x20
(1) make each column(coordinate x, coordinate y, … lattice parameter a …) 20x1 embedding.
(2) make weights vector(20x1)
(3) matrix multiplication (1) and (2). then I get 20x20 matrix.
(4) Compare that 20x20 matrix with corresponding graph_Image
(5) Use GDS ~~ also neural network.
The idea that make just raw numerical value dataset into matrix by embedding.
Does it make sense? or my method is wrong in someway?
thanks a lot.
Have a good day