Tag: neural differential equations
All the talks with the tag "neural differential equations".
Online Dynamics Learning for Predictive Control with an Application to Aerial Robots
Rishi Raj SahooPublished: at 11:00 AMThis work presents an online dynamics learning framework to improve the accuracy of model predictive control (MPC) during deployment. Using knowledge-based neural ODEs (KNODEs) and transfer learning techniques, the model continually adapts to disturbances, demonstrated through simulations and quadrotor experiments. Results show improved trajectory tracking under varying conditions.
An Introduction to Neural Differential Equations
Jyotirmaya ShivottamPublished: at 10:00 AMThis talk outlines the basics of Neural Differential Equations (NDEs), starting with the foundational paper by Chen et al. on Neural Ordinary Differential Equations (NODEs) and explores connections with dynamical modeling. It presents some examples of neural architectures in the NDE framework and discusses the universal approximation and expressivity properties of certain NDEs, in the context of the manifold hypothesis. The talk concludes with practical considerations for implementing NDE networks.