[D] Falsified results with Deep learning
Hi everyone !
I am looking for papers that would show that deep learning can “invent” things, especially in the domain of super-resolution/upsampling. I only find papers that boasts the merits of their method, but not papers that show that their network can mistake high frequency features and noise or stuff like that…
submitted by /u/luciolis