Zobrazeno 1 - 10
of 485
pro vyhledávání: '"Rakhsha, A"'
The Value Iteration (VI) algorithm is an iterative procedure to compute the value function of a Markov decision process, and is the basis of many reinforcement learning (RL) algorithms as well. As the error convergence rate of VI as a function of ite
Externí odkaz:
http://arxiv.org/abs/2407.10454
Long-horizon tasks, which have a large discount factor, pose a challenge for most conventional reinforcement learning (RL) algorithms. Algorithms such as Value Iteration and Temporal Difference (TD) learning have a slow convergence rate and become in
Externí odkaz:
http://arxiv.org/abs/2407.08803
Autor:
Salavatidezfouli, Sajad, Rakhsha, Saeid, Sheidani, Armin, Stabile, Giovanni, Rozza, Gianluigi
This paper aims to comprehensively investigate the efficacy of various Model Order Reduction (MOR) and deep learning techniques in predicting heat transfer in a pulsed jet impinging on a concave surface. Expanding on the previous experimental and num
Externí odkaz:
http://arxiv.org/abs/2402.10641
We introduce new planning and reinforcement learning algorithms for discounted MDPs that utilize an approximate model of the environment to accelerate the convergence of the value function. Inspired by the splitting approach in numerical linear algeb
Externí odkaz:
http://arxiv.org/abs/2211.13937
Publikováno v:
In Cancer / Radiothérapie December 2024 28(8):650-656
Autor:
Rakhsha, Fayez, Hatami, Shahabeddin, Gorji Azandariani, Mojtaba, Alipour Mansourkhani, Ali, Davani, Mohammadreza
Publikováno v:
In Structures December 2024 70
Autor:
Rakhsha, Amirhossein a, Eslami, Reza a, Yang, Xiaoxuan a, Noor, Navid a, Ismail, Fatma M. a, Abdellah, Ahmed M. a, b, Soleymani, Leyla c, d, e, f, ⁎⁎, Higgins, Drew a, ⁎
Publikováno v:
In Nano Energy January 2025 133
Autor:
Navid Noor, Thomas Baker, Hyejin Lee, Elliot Evans, Shayan Angizi, Jeffrey Daniel Henderson, Amirhossein Rakhsha, Drew Higgins
Publikováno v:
ACS Omega, Vol 9, Iss 9, Pp 10080-10089 (2024)
Externí odkaz:
https://doaj.org/article/e319af2f7d3143958fd6560324f769fb
Autor:
Ahmed M. Abdellah, Fatma Ismail, Oliver W. Siig, Jie Yang, Carmen M. Andrei, Liza-Anastasia DiCecco, Amirhossein Rakhsha, Kholoud E. Salem, Kathryn Grandfield, Nabil Bassim, Robert Black, Georg Kastlunger, Leyla Soleymani, Drew Higgins
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-15 (2024)
Abstract Electrochemical conversion of CO2 offers a sustainable route for producing fuels and chemicals. Pd-based catalysts are effective for converting CO2 into formate at low overpotentials and CO/H2 at high overpotentials, while undergoing poorly
Externí odkaz:
https://doaj.org/article/d1c7a154f14b4fbe8002d7f284550e96