Viktor Nilsson

Doctoral Student in Applied Mathematics. My research concerns applications of probability theory to problems arising in machine learning. Broadly, I am interested in the theory of large deviations, optimal transport, information theory, and generative models such as diffusion models and GANs.

I am funded by the Wallenberg Autonomous Systems Program (WASP).