Abstract: Trajectory prediction is a crucial task required for autonomous driving. The highly interactions and uncertainties in real-world traffic scenarios make it a challenge to generate ...

Abstract: This letter presents a theoretical framework for estimating the trajectory-based region of attraction in nonlinear higher-order networks. A Lyapunov-based criterion is established for ...

We propose a novel multi-pose loss function to train a neural network for 6D pose estimation, using synthetic data and evaluating it on real images. Our loss is inspired by the VSD (Visible Surface ...

The vision is to create a package for finite volume simulation with applications to geophysical imaging and subsurface flow. To enable the understanding of the many different components, this package ...