63 citations · 271 across the 36 of their papers we have counts for
65 papers
Gaussian Process Barrier States for Safe Trajectory Optimization and Control
Hassan Almubarak, Manan Gandhi, Yuichiro Aoyama +2
This paper proposes embedded Gaussian Process Barrier States (GP-BaS), a methodology to safely control unmodeled dynamics of nonlinear system using Bayesian learning. Gaussian Proc…
Sampling-Based Optimization for Multi-Agent Model Predictive Control
Ziyi Wang, Augustinos D. Saravanos, Hassan Almubarak +2
We systematically review the Variational Optimization, Variational Inference and Stochastic Search perspectives on sampling-based dynamic optimization and discuss their connections…
Solving Feynman-Kac Forward Backward SDEs Using McKean-Markov Branched Sampling
Kelsey P. Hawkins, Ali Pakniyat, Evangelos Theodorou +1
We propose a new method for the numerical solution of the forward-backward stochastic differential equations (FBSDE) appearing in the Feynman-Kac representation of the value functi…
Data-driven discovery of non-Newtonian astronomy via learning non-Euclidean Hamiltonian
Oswin So, Gongjie Li, Evangelos A. Theodorou +1
Incorporating the Hamiltonian structure of physical dynamics into deep learning models provides a powerful way to improve the interpretability and prediction accuracy. While previo…
Deep Generalized Schrödinger Bridge
Guan-Horng Liu, Tianrong Chen, Oswin So +1
Mean-Field Game (MFG) serves as a crucial mathematical framework in modeling the collective behavior of individual agents interacting stochastically with a large population. In thi…
Deep Graphic FBSDEs for Opinion Dynamics Stochastic Control
Tianrong Chen, Ziyi Wang, Evangelos A. Theodorou
In this paper, we present a scalable deep learning approach to solve opinion dynamics stochastic optimal control problems with mean field term coupling in the dynamics and cost fun…