Zobrazeno 1 - 10
of 13 025
pro vyhledávání: '"A Theodorou"'
Autor:
Theodoropoulos, Panagiotis, Komianos, Nikolaos, Pacelli, Vincent, Liu, Guan-Horng, Theodorou, Evangelos A.
Recent advancements in diffusion bridges for distribution transport problems have heavily relied on matching frameworks, yet existing methods often face a trade-off between scalability and access to optimal pairings during training. Fully unsupervise
Externí odkaz:
http://arxiv.org/abs/2410.14055
This paper provides an overview, analysis, and comparison of second-order dynamic optimization algorithms, i.e., constrained Differential Dynamic Programming (DDP) and Sequential Quadratic Programming (SQP). Although a variety of these algorithms has
Externí odkaz:
http://arxiv.org/abs/2409.11649
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, Tube-Model Predictive Path Integral Control, and Robust Model Predict
Externí odkaz:
http://arxiv.org/abs/2409.07563
We present a novel second-order trajectory optimization algorithm based on Stein Variational Newton's Method and Maximum Entropy Differential Dynamic Programming. The proposed algorithm, called Stein Variational Differential Dynamic Programming, is a
Externí odkaz:
http://arxiv.org/abs/2409.04644
Sociotechnical requirements shape the governance of artificially intelligent (AI) systems. In an era where embodied AI technologies are rapidly reshaping various facets of contemporary society, their inherent dynamic adaptability presents a unique bl
Externí odkaz:
http://arxiv.org/abs/2409.00015
Variable autonomy equips a system, such as a robot, with mixed initiatives such that it can adjust its independence level based on the task's complexity and the surrounding environment. Variable autonomy solves two main problems in robotic planning:
Externí odkaz:
http://arxiv.org/abs/2407.16254
The generative modeling of data on manifold is an important task, for which diffusion models in flat spaces typically need nontrivial adaptations. This article demonstrates how a technique called `trivialization' can transfer the effectiveness of dif
Externí odkaz:
http://arxiv.org/abs/2405.16381
Autor:
Duan, Chenru, Liu, Guan-Horng, Du, Yuanqi, Chen, Tianrong, Zhao, Qiyuan, Jia, Haojun, Gomes, Carla P., Theodorou, Evangelos A., Kulik, Heather J.
Transition states (TSs) are transient structures that are key in understanding reaction mechanisms and designing catalysts but challenging to be captured in experiments. Alternatively, many optimization algorithms have been developed to search for TS
Externí odkaz:
http://arxiv.org/abs/2404.13430
This article considers the generative modeling of the (mixed) states of quantum systems, and an approach based on denoising diffusion model is proposed. The key contribution is an algorithmic innovation that respects the physical nature of quantum st
Externí odkaz:
http://arxiv.org/abs/2404.06336
Autor:
Vlahov, Bogdan, Gibson, Jason, Fan, David D., Spieler, Patrick, Agha-mohammadi, Ali-akbar, Theodorou, Evangelos A.
Publikováno v:
IEEE Robotics and Automation Letters, vol. 9, no. 5, pp.4543-4550, 2024
Sampling-based model-predictive controllers have become a powerful optimization tool for planning and control problems in various challenging environments. In this paper, we show how the default choice of uncorrelated Gaussian distributions can be im
Externí odkaz:
http://arxiv.org/abs/2404.03094