Overparametrization helps offline-to-online generalization of closed-loop control from pixels
Mathias Lechner,Ramin Hasani,Alexander Amini,Tsun-Hsuan Wang,Thomas A. Henzinger,Daniela Rus,Mathias Lechner,Ramin Hasani,Alexander Amini,Tsun-Hsuan Wang,Thomas A. Henzinger,Daniela Rus
There is an ever-growing zoo of modern neural network models that can efficiently learn end-to-end control from visual observations. These advanced deep models, ranging from convolutional to Vision Transformers, from small to gigantic networks, have been extensively tested on offline image classification tasks. In this paper, we study these vision models with respect to the open-loop training to c...
