Re:Computer Vision Research: The deep “depression”
by webaba on Thursday June 09, 2016 @11:25AM
(#11870007)
Completely agree with this viewpoint. Explanatory power and reproducibility are two of the most important aspects of a scientific paper. Most deep learning based papers lack both these properties.
Re:Computer Vision Research: The deep “depression”
by wolfgke on Thursday June 09, 2016 @11:44AM
(#11870138)
> Explanatory power and reproducibility are two of the most important aspects of a scientific paper.
The reproducability problem should be solvable if the authors would simply release the training data and source code that trains the network (as yould scientific practise would require). Or is there anything else that is necessary to assure reproducability (I'm not that deep into CV papers)?
One does science also to understand why something works (i.e. what is the theory behind it). Deep learning gives something that (perhaps) works, but doesn't give an any clue to the question why it works - on what theory does the neural net internally compute in its black box.
Based on this criterion one can even argue that deep learning papers should not be considered as science as long as the authors of the deep learning paper make no really hard attempt to present at least a partly understanding of the internal theory that the trained neuronal network executes (i.e. a very detailed interpretation of the weights with ideally falsifiable predictions). This is hard work, I know, but isn't that nearly anything in science?