3 citations · 3 across the 6 of their papers we have counts for
6 papers
Stochastic optimization for learning quantum state feedback control
Ethan N. Evans, Ziyi Wang, Adam G. Frim +2
High fidelity state preparation represents a fundamental challenge in the application of quantum technology. While the majority of optimal control approaches use feedback to improv…
Spatio-Temporal Differential Dynamic Programming for Control of Fields
Ethan N. Evans, Oswin So, Andrew P. Kendall +2
We consider the optimal control problem of a general nonlinear spatio-temporal system described by Partial Differential Equations (PDEs). Theory and algorithms for control of spati…
Stochastic Spatio-Temporal Optimization for Control and Co-Design of Systems in Robotics and Applied Physics
Ethan N. Evans, Andrew P. Kendall, Evangelos A. Theodorou
Correlated with the trend of increasing degrees of freedom in robotic systems is a similar trend of rising interest in Spatio-Temporal systems described by Partial Differential Equ…
Spatio-Temporal Stochastic Optimization: Theory and Applications to Optimal Control and Co-Design
Ethan N. Evans, Andrew P. Kendall, George I. Boutselis +1
There is a rising interest in Spatio-temporal systems described by Partial Differential Equations (PDEs) among the control community. Not only are these systems challenging to cont…
Variational Optimization Based Reinforcement Learning for Infinite Dimensional Stochastic Systems
Ethan N. Evans, Marcus A. Pereira, George I. Boutselis +1
Systems involving Partial Differential Equations (PDEs) have recently become more popular among the machine learning community. However prior methods usually treat infinite dimensi…
Leveraging Stochasticity for Open Loop and Model Predictive Control of Complex Fluid Systems
George I. Boutselis, Ethan N. Evans, Marcus A. Pereira +1
Stochastic Spatio-Temporal processes are prevalent across domains ranging from modeling of plasma to the turbulence in fluids to the wave function of quantum systems. This letter s…