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pro vyhledávání: '"Litvinenko, Alexander"'
We use the Multi Level Monte Carlo method to estimate uncertainties in a Henry-like salt water intrusion problem with a fracture. The flow is induced by the variation of the density of the fluid phase, which depends on the mass fraction of salt. We a
Externí odkaz:
http://arxiv.org/abs/2404.18003
Autor:
Logashenko, Dmitry, Litvinenko, Alexander, Tempone, Raul, Vasilyeva, Ekaterina, Wittum, Gabriel
Publikováno v:
Journal of Computational Physics, Volume 503, 2024, 112854
We investigate the applicability of the well-known multilevel Monte Carlo (MLMC) method to the class of density-driven flow problems, in particular the problem of salinisation of coastal aquifers. As a test case, we solve the uncertain Henry saltwate
Externí odkaz:
http://arxiv.org/abs/2403.17018
Autor:
Litvinenko, Alexander, Logashenko, Dmitry, Tempone, Raul, Vasilyeva, Ekaterina, Wittum, Gabriel
We consider a class of density-driven flow problems. We are particularly interested in the problem of the salinization of coastal aquifers. We consider the Henry saltwater intrusion problem with uncertain porosity, permeability, and recharge paramete
Externí odkaz:
http://arxiv.org/abs/2302.07804
Autor:
Lozina Yuliya, Litvinenko Alexander
Publikováno v:
π-Economy, Vol 17, Iss 3 (2024)
Relevance. Intellectual property is defined as one of the main elements and catalysts of scientific and technological development of the country. On the way to an innovative and sustainable future, the protection of intellectual property is a key ele
Externí odkaz:
https://doaj.org/article/71db3c2b71c1497fb7598c058ecb7bec
Autor:
Litvinenko, Alexander, Marzouk, Youssef, Matthies, Hermann G., Scavino, Marco, Spantini, Alessio
Very often, in the course of uncertainty quantification tasks or data analysis, one has to deal with high-dimensional random variables (RVs). A high-dimensional RV can be described by its probability density (pdf) and/or by the corresponding probabil
Externí odkaz:
http://arxiv.org/abs/2111.07164
Statistical analysis of massive datasets very often implies expensive linear algebra operations with large dense matrices. Typical tasks are an estimation of unknown parameters of the underlying statistical model and prediction of missing values. We
Externí odkaz:
http://arxiv.org/abs/2104.07146
We solve a weakly supervised regression problem. Under "weakly" we understand that for some training points the labels are known, for some unknown, and for others uncertain due to the presence of random noise or other reasons such as lack of resource
Externí odkaz:
http://arxiv.org/abs/2104.06548
Scientific computations or measurements may result in huge volumes of data. Often these can be thought of representing a real-valued function on a high-dimensional domain, and can be conceptually arranged in the format of a tensor of high degree in s
Externí odkaz:
http://arxiv.org/abs/1906.05669