2022
Explicit Disentanglement of Appearance and Perspective in Generative Models, Nicki Skafte Detlefsen, Søren Hauberg. In Proceedings IEEE Conf. on Neural Information Processing Systems (Neurips), Vancouver, Canada. December 2019.
Reliable training and estimation of variance networks, Nicki Skafte Detlefsen, Martin Jørgensen, Søren Hauberg. In Proceedings IEEE Conf. on Neural Information Processing Systems (Neurips), Vancouver, Canada. December 2019.
Diffeomorphic Temporal Alignment Nets, Ron A. Shapira Weber, Matan Eyal, Nicki Skafte Detlefsen, Oren Shriki, Oren Freifeld. In Proceedings IEEE Conf. on Neural Information Processing Systems (Neurips), Vancouver, Canada. December 2019.
Machine Learning Operations
Introduce the student to a number of coding practices that will help them organization, scale, monitor and deploy machine learning models either in a research or production setting. To provide hands-on experience with a number of frameworks, both local and in the cloud, for doing large scale machine learning models.
Course webpage: https://skaftenicki.github.io/dtu_mlops/
DTU course database: https://kurser.dtu.dk/course/02476