62 citations · 71 across the 10 of their papers we have counts for
11 papers
Towards Compute-Optimal Many-Shot In-Context Learning
Shahriar Golchin, Yanfei Chen, Rujun Han +7
Long-context large language models (LLMs) are able to process inputs containing up to several million tokens. In the scope of in-context learning (ICL), this translates into using…
MPPI-Generic: A CUDA Library for Stochastic Trajectory Optimization
Bogdan Vlahov, Jason Gibson, Manan Gandhi +1
This paper introduces a new C++/CUDA library for GPU-accelerated stochastic optimization called MPPI-Generic. It provides implementations of Model Predictive Path Integral control,…
Safe Importance Sampling in Model Predictive Path Integral Control
Manan Gandhi, Hassan Almubarak, Evangelos Theodorou
We introduce the notion of importance sampling under embedded barrier state control, titled Safety Controlled Model Predictive Path Integral Control (SC-MPPI). For robotic systems…
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…
Safety in Augmented Importance Sampling: Performance Bounds for Robust MPPI
Manan Gandhi, Hassan Almubarak, Yuichiro Aoyama +1
This work explores the nature of augmented importance sampling in safety-constrained model predictive control problems. When operating in a constrained environment, sampling based…
Robustifying Reinforcement Learning Policies with Adaptive Control
Yikun Cheng, Pan Zhao, Manan Gandhi +3
A reinforcement learning (RL) policy trained in a nominal environment could fail in a new/perturbed environment due to the existence of dynamic variations. Existing robust methods…
Variational Inference MPC using Tsallis Divergence
Ziyi Wang, Oswin So, Jason Gibson +4
In this paper, we provide a generalized framework for Variational Inference-Stochastic Optimal Control by using thenon-extensive Tsallis divergence. By incorporating the deformed e…
Robust Model Predictive Path Integral Control: Analysis and Performance Guarantees
Manan Gandhi, Bogdan Vlahov, Jason Gibson +2
In this paper we propose a novel decision making architecture for Robust Model Predictive Path Integral control (RMPPI) and investigate its performance guarantees and applicability…
Propagating Uncertainty through the tanh Function with Application to Reservoir Computing
Manan Gandhi, Keuntaek Lee, Yunpeng Pan +1
Many neural networks use the tanh activation function, however when given a probability distribution as input, the problem of computing the output distribution in neural networks w…
Pseudospectral Model Predictive Control under Partially Learned Dynamics
Manan Gandhi, Yunpeng Pan, Evangelos Theodorou
Trajectory optimization of a controlled dynamical system is an essential part of autonomy, however many trajectory optimization techniques are limited by the fidelity of the underl…
Trajectory Optimization Algorithm Studies
Manan Gandhi
In complex engineered systems, completing an objective is sometimes not enough. The system must be able to reach a set performance characteristic, such as an unmanned aerial vehicl…