Dear Ghobani,
I checked your Mathematica codes and found that your KAN model does not reduce the loss. It seems that only one KANlayer[2,1,15,3] is not complex enough to learn.
kan = NetTrain[NetChain[{KANlayer[2,1,15,3]},"Input"->2],training]
I added one more KANlayer, then the loss is reduced.
dataSDL = ArrayReshape[N@Range[300], {100, 3}];
Two KANlayers:
kanSDLEE =
NetTrain[NetChain[{KANlayer[2, 5, 15, 3], KANlayer[5, 1, 15, 3]}],
dataSDL[[All, 1 ;; 2]] -> Transpose@{dataSDL[[All, 3]]}].
Three KAN layers:
kanSDLEE03 =
NetTrain[
NetChain[{KANlayer[2, 5, 15, 3], KANlayer[5, 5, 15, 3],
KANlayer[5, 1, 15, 3]}],
dataSDL[[All, 1 ;; 2]] -> Transpose@{dataSDL[[All, 3]]}].
