Marin Bilos

Nov 21, 2024 | amazon.science | Joanna Sommer |Syama Sundar Rangapuram |Tim Januschowski |Marin Bilos

Marin Bilos, Joanna Sommer, Syama Rangapuram, Tim Januschowski, Stephan Günnemann Copy BibTeX Neural ordinary differential equations describe how values change in time. This is the reason why they gained importance in modeling sequential data, especially when the observations are made at irregular intervals. In this paper we propose an alternative by directly modeling the solution curves — the flow of an ODE — with a neural network.

Nov 21, 2024 | amazon.science | Joanna Sommer |Syama Sundar Rangapuram |Tim Januschowski |Marin Bilos

Marin Bilos, Joanna Sommer, Syama Rangapuram, Tim Januschowski, Stephan Günnemann Copy BibTeX Neural ordinary differential equations describe how values change in time. This is the reason why they gained importance in modeling sequential data, especially when the observations are made at irregular intervals. In this paper we propose an alternative by directly modeling the solution curves — the flow of an ODE — with a neural network.