8 citations · 8 across the 6 of their papers we have counts for
3 papers · 1 filter
Variational Inference via Entropic Transport Descent
Vincent Pacelli, Akash Ratheesh, Evangelos Theodorou
Particle-based variational inference (ParVI) methods approximate an intractable target distribution by evolving an ensemble of interacting samples. Existing approaches rely predomi…
Beyond Pure Sampling: Hybrid Optimization Mechanisms for Non-Convex Model Predictive Control
Yuichiro Aoyama, Minchan Jung, Akash Ratheesh +1
This paper investigates the optimization mechanisms of non-convex Model Predictive Control (MPC) using the Maximum Entropy Differential Dynamic Programming (ME-DDP) framework. Navi…
Sampling-Based Control via Entropy-Regularized Optimal Transport
Vincent Pacelli, Akash Ratheesh, Evangelos A. Theodorou
Sampling-based model predictive control methods like MPPI and CEM are essential for real-time control of nonlinear robotic systems, particularly where discontinuous dynamics preclu…