5 citations · 6 across the 2 of their papers we have counts for
5 papers
Parameter-Conditioned Sequential Generative Modeling of Fluid Flows
Jeremy Morton, Freddie D. Witherden, Mykel J. Kochenderfer
The computational cost associated with simulating fluid flows can make it infeasible to run many simulations across multiple flow conditions. Building upon concepts from generative…
Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control
Jeremy Morton, Freddie D Witherden, Mykel J Kochenderfer
Koopman theory asserts that a nonlinear dynamical system can be mapped to a linear system, where the Koopman operator advances observations of the state forward in time. However, t…
Deep Dynamical Modeling and Control of Unsteady Fluid Flows
Jeremy Morton, Freddie D. Witherden, Antony Jameson +1
The design of flow control systems remains a challenge due to the nonlinear nature of the equations that govern fluid flow. However, recent advances in computational fluid dynamics…
Multi-Agent Imitation Learning for Driving Simulation
Raunak P. Bhattacharyya, Derek J. Phillips, Blake Wulfe +3
Simulation is an appealing option for validating the safety of autonomous vehicles. Generative Adversarial Imitation Learning (GAIL) has recently been shown to learn representative…
Imitating Driver Behavior with Generative Adversarial Networks
Alex Kuefler, Jeremy Morton, Tim Wheeler +1
The ability to accurately predict and simulate human driving behavior is critical for the development of intelligent transportation systems. Traditional modeling methods have emplo…