7 citations · 10 across the 3 of their papers we have counts for
8 papers
Adaptive Risk Sensitive Model Predictive Control with Stochastic Search
Ziyi Wang, Oswin So, Keuntaek Lee +2
We present a general framework for optimizing the Conditional Value-at-Risk for dynamical systems using stochastic search. The framework is capable of handling the uncertainty from…
Approximate Inverse Reinforcement Learning from Vision-based Imitation Learning
Keuntaek Lee, Bogdan Vlahov, Jason Gibson +2
In this work, we present a method for obtaining an implicit objective function for vision-based navigation. The proposed methodology relies on Imitation Learning, Model Predictive…
Sample-based Distributional Policy Gradient
Rahul Singh, Keuntaek Lee, Yongxin Chen
Distributional reinforcement learning (DRL) is a recent reinforcement learning framework whose success has been supported by various empirical studies. It relies on the key idea of…
Aggressive Perception-Aware Navigation using Deep Optical Flow Dynamics and PixelMPC
Keuntaek Lee, Jason Gibson, Evangelos A. Theodorou
Recently, vision-based control has gained traction by leveraging the power of machine learning. In this work, we couple a model predictive control (MPC) framework to a visual pipel…
Deep Forward-Backward SDEs for Min-max Control
Ziyi Wang, Keuntaek Lee, Marcus A. Pereira +2
This paper presents a novel approach to numerically solve stochastic differential games for nonlinear systems. The proposed approach relies on the nonlinear Feynman-Kac theorem tha…
Ensemble Bayesian Decision Making with Redundant Deep Perceptual Control Policies
Keuntaek Lee, Ziyi Wang, Bogdan I. Vlahov +2
This work presents a novel ensemble of Bayesian Neural Networks (BNNs) for control of safety-critical systems. Decision making for safety-critical systems is challenging due to per…