Famous neural networks for regression
I have come across many neural network architecture for classification problems. AlexNet, ResNet, VGGNet, GoogLeNet etc... Is there similar networks for regression problems which can be used for transfer learning? 

Alright, all those architecture are not only for classification, the only shift you have to make for modifying a DL model from classification to regression is to change the top layer. For example in the VGGNET the last layer could be :

Dense(25, activation='softmax')


That means that we want to predict 25 outputs with a probability distribution (classification)

But it could be 

Dense(1, activation='linear')


With the exact same architecture, it will output a number (regression)

So in the case of transfer learning you can just take an existing architecture that is pretrained on classification tasks, remove the top layer and do whatever you want.
