Results 41 to 50 of about 217,226 (371)
DLGA-PDE: Discovery of PDEs with incomplete candidate library via combination of deep learning and genetic algorithm [PDF]
Journal of Computational Physics, 2020 Data-driven methods have recently been developed to discover underlying partial differential equations (PDEs) of physical problems. However, for these methods, a complete candidate library of potential terms in a PDE are usually required.
Hao Xu, Haibin Chang, Dongxiao Zhang
semanticscholar +1 more source
Dynamic differences between DNA damage repair responses in primary tumors and cell lines
Translational Oncology, 2021 The study of DNA damage repair response (DDR) in prostate cancer is restricted by the limited number of prostate cancer cell lines and lack of surrogates for heterogeneity in clinical samples.
Collin Gilbreath +11 more
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Plasma desmosine for prediction of outcomes after acute myocardial infarction
Frontiers in Cardiovascular Medicine, 2022 BackgroundElastin degradation is implicated in the pathology of vulnerable plaque. Recent studies show promising results for plasma desmosine (pDES), an elastin-specific degradation product, as a marker of cardiovascular disease (CVD) outcomes.
Kashan Ali +9 more
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Semi-Lagrangian discontinuous Galerkin schemes for some first and second-order partial differential equations [PDF]
, 2015 Explicit, unconditionally stable, high-order schemes for the approximation of some first- andsecond-order linear, time-dependent partial differential equations (PDEs) are proposed.The schemes are based on a weak formulation of a semi-Lagrangian scheme ...
Bokanowski, Olivier +1 more
core +4 more sources
پژوهشهای ریاضی, 2021 In this paper, we consider a generalized form of nonlinear Radhakrishnan-Kundu-Lakshmanan equation. The generalized exponential rational function method has been used to obtain some novel exact optical solutions.
Behzad Ghanbari
doaj
KoopmanLab: Machine learning for solving complex physics equations
APL Machine Learning, 2023 Numerous physics theories are rooted in partial differential equations (PDEs). However, the increasingly intricate physics equations, especially those that lack analytic solutions or closed forms, have impeded the further development of physics ...
Wei Xiong +5 more
doaj +1 more source
Solve High-Dimensional Reflected Partial Differential Equations by Neural Network Method
Mathematical and Computational Applications, 2023 Reflected partial differential equations (PDEs) have important applications in financial mathematics, stochastic control, physics, and engineering. This paper aims to present a numerical method for solving high-dimensional reflected PDEs.
Xiaowen Shi +3 more
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Dispersionless integrable systems in 3D and Einstein-Weyl geometry [PDF]
, 2013 For several classes of second order dispersionless PDEs, we show that the symbols of their formal linearizations define conformal structures which must be Einstein-Weyl in 3D (or self-dual in 4D) if and only if the PDE is integrable by the method of ...
Ferapontov, Eugene, Kruglikov, Boris
core +2 more sources
Approximation Error Analysis of Some Deep Backward Schemes for Nonlinear PDEs [PDF]
SIAM Journal on Scientific Computing, 2020 Recently proposed numerical algorithms for solving high-dimensional nonlinear partial differential equations (PDEs) based on neural networks have shown their remarkable performance. We review some of them and study their convergence properties.
Maximilien Germain, H. Pham, X. Warin
semanticscholar +1 more source
Boundary Value Problems, 2020 In this paper, we prove the global existence and exponential energy decay results of a coupled Lamé system with distributed time delay, nonlinear source term, and without memory term by using the Faedo–Galerkin method.
Salah Boulaaras, Nadjat Doudi
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