Zobrazeno 1 - 10
of 542
pro vyhledávání: '"Khammash Mustafa"'
Motivated by the increasing popularity of overparameterized Stochastic Differential Equations (SDEs) like Neural SDEs, Wang, Blanchet and Glynn recently introduced the generator gradient estimator, a novel unbiased stochastic gradient estimator for S
Externí odkaz:
http://arxiv.org/abs/2407.20196
Stochastic filtering is a vibrant area of research in both control theory and statistics, with broad applications in many scientific fields. Despite its extensive historical development, there still lacks an effective method for joint parameter-state
Externí odkaz:
http://arxiv.org/abs/2311.00836
Perfect adaptation is a phenomenon whereby the output variables of a system can maintain certain values despite external disturbances. Robust perfect adaptation (RPA) refers to an adaptation property that does not require fine-tuning of system parame
Externí odkaz:
http://arxiv.org/abs/2307.07444
Autor:
Briat, Corentin, Khammash, Mustafa
While noise is generally associated with uncertainties and often has a negative connotation in engineering, living organisms have evolved to adapt to (and even exploit) such uncertainty to ensure the survival of a species or implement certain functio
Externí odkaz:
http://arxiv.org/abs/2209.13901
Autor:
Briat, Corentin, Khammash, Mustafa
The innocuousness property of a controller is that property that makes the closed-loop system stable regardless the values of the controller parameters. In other words, the closed-loop system exhibits some structural stability property with respect t
Externí odkaz:
http://arxiv.org/abs/2201.13375
Publikováno v:
In Biotechnology Advances July-August 2024 73
The design and implementation of regulation motifs ensuring robust perfect adaptation are challenging problems in synthetic biology. Indeed, the design of high-yield robust metabolic pathways producing, for instance, drug precursors and biofuels, cou
Externí odkaz:
http://arxiv.org/abs/2112.10273
Autor:
Briat, Corentin, Khammash, Mustafa
Stochastic reaction networks is a powerful class of models for the representation a wide variety of population models including biochemistry. The control of such networks has been recently considered due to their important implications for the contro
Externí odkaz:
http://arxiv.org/abs/2111.14754
Filtering for stochastic reaction networks (SRNs) is an important problem in systems/synthetic biology aiming to estimate the state of unobserved chemical species. A good solution to it can provide scientists valuable information about the hidden dyn
Externí odkaz:
http://arxiv.org/abs/2110.07746
In the past few decades, the development of fluorescent technologies and microscopic techniques has greatly improved scientists' ability to observe real-time single-cell activities. In this paper, we consider the filtering problem associate with thes
Externí odkaz:
http://arxiv.org/abs/2106.03276