Results 181 to 190 of about 646,451 (325)
The Fundamental Theorem of Vassiliev Invariants [PDF]
, 1997 Dror Bar-Natan, A. Stoimenow
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Asian Journal of Control, EarlyView.Abstract Large swarms often adopt a hierarchical network structure that incorporates information aggregation. Although this approach offers significant advantages in terms of communication efficiency and computational complexity, it can also lead to degradation due to information constraints.
Kento Fujita, Daisuke Tsubakino
wiley +1 more source
A Sharp Quantitative Alexandrov Inequality and Applications to Volume Preserving Geometric Flows in 3D. [PDF]
Arch Ration Mech AnalJulin V, Morini M, Oronzio F, Spadaro E.
europepmc +1 more source
Risk‐aware safe reinforcement learning for control of stochastic linear systems
Asian Journal of Control, EarlyView.Abstract This paper presents a risk‐aware safe reinforcement learning (RL) control design for stochastic discrete‐time linear systems. Rather than using a safety certifier to myopically intervene with the RL controller, a risk‐informed safe controller is also learned besides the RL controller, and the RL and safe controllers are combined together ...
Babak Esmaeili +2 more
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Fundamental theorems for the log minimal model program [PDF]
, 2009 Osamu Fujino
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Modeling and parameter estimation for fractional large‐scale interconnected Hammerstein systems
Asian Journal of Control, EarlyView.Abstract This paper addresses the challenge of modeling and identifying large‐scale interconnected systems exhibiting memory effects, hereditary properties, and non‐local interactions. We propose a fractional‐order extension of the Hammerstein architecture that incorporates Grünwald–Letnikov operators to capture complex dynamics through multiple ...
Mourad Elloumi +2 more
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Heritage of Arabic Geometry: Al–Samarqandī’s Work in Fundamental Geometric Theorems
, 2023 Wesam TALAB
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Generative Deep Learning for Advanced Battery Materials
Batteries &Supercaps, EarlyView.This review explores the role of generative deep learning (DL) in battery materials analysis and highlights the fundamental principles of generative DL and its applications in designing battery materials. The importance of using multimodal data is underscored to effectively address the challenges faced during the development of battery materials across
Deepalaxmi Rajagopal +3 more
wiley +1 more source