In the thesis, I explore how we can make discrete structures like algorithms differentiable. [1/13]
By making algorithms differentiable, we can integrate them end-to-end into neural network machine learning architectures. For example, we can continuously relax sorting (github.com/Felix-Petersen…) for learning to rank. [2/13]