Prof. Dr. Thomas Brox

Deep learning has been getting large attention in science and the media. In my talk I will show results mainly from computer vision that explain this attention and indicates how things could go on in the future. The talk will consist of three main parts. In the first part, I will give a brief introduction into the fundamentals of deep learning, such as common network architectures and the basic back-propagation algorithm for optimization of their parameters. In the second part, I will show recent results from my group, which developed for the first time learning formulations for 3D computer vision. In the third part, I will list mathematical challenges in deep learning, the solution of which would probably largely improve the state of the art.