Results 1 to 10 of about 3,651,563 (307)
Learning the solution operator of parametric partial differential equations with physics-informed DeepONets [PDF]
Science Advances, 2021 Enabling the rapid emulation of parametric differential equations with physics-informed deep operator networks.
Sifan Wang, Hanwen Wang
exaly +2 more sources
Transformer for Partial Differential Equations' Operator Learning [PDF]
Trans. Mach. Learn. Res., 2022 Data-driven learning of partial differential equations' solution operators has recently emerged as a promising paradigm for approximating the underlying solutions.
Zijie Li, Kazem Meidani, A. Farimani
semanticscholar +1 more source
Physics-Informed Neural Operator for Learning Partial Differential Equations [PDF]
ACM / IMS Journal of Data Science, 2021 In this paper, we propose physics-informed neural operators (PINO) that combine training data and physics constraints to learn the solution operator of a given family of parametric Partial Differential Equations (PDE).
Zong-Yi Li +7 more
semanticscholar +1 more source
In-context operator learning with data prompts for differential equation problems [PDF]
Proceedings of the National Academy of Sciences of the United States of America, 2023 Significance This paper presents In-Context Operator Networks (ICON), a neural network approach that can learn new operators from prompted data during the inference stage without requiring any weight updates.
Liu Yang +3 more
semanticscholar +1 more source
A nonlocal physics-informed deep learning framework using the peridynamic differential operator [PDF]
arXiv.org, 2020 The Physics-Informed Neural Network (PINN) framework introduced recently incorporates physics into deep learning, and offers a promising avenue for the solution of partial differential equations (PDEs) as well as identification of the equation parameters.
E. Haghighat +3 more
semanticscholar +1 more source
Integro-differential equations with bounded operators in Banach spaces [PDF]
Қарағанды университетінің хабаршысы. Математика сериясы, 2022 The paper investigates integro-differential equations in Banach spaces with operators, which are a composition of convolution and differentiation operators.
V.E. Fedorov, A.D. Godova, B.T. Kien
doaj +3 more sources
Demonstratio Mathematica, 2021 In this work, we develop and analyze an explicit finite volume scheme for a one-dimensional nonlinear, degenerate, convection–diffusion equation having application in petroleum reservoir.
Mostefai Mohamed Lamine +2 more
doaj +1 more source
A Class of Symmetric Fractional Differential Operator Formed by Special Functions
Journal of Mathematics, 2022 In light of a certain sort of fractional calculus, a generalized symmetric fractional differential operator based on Raina’s function is built. The generalized operator is then used to create a formula for analytic functions of type normalized.
Ibtisam Aldawish +2 more
doaj +1 more source
Advances in Mathematical Physics, 2021 In this paper, a beta operator is used with Caputo Marichev-Saigo-Maeda (MSM) fractional differentiation of extended Mittag-Leffler function in terms of beta function.
Tayyaba Manzoor +3 more
doaj +1 more source
Discrete Dynamics in Nature and Society, 2021 In this paper, the Laplace operator is used with Caputo-Type Marichev–Saigo–Maeda (MSM) fractional differentiation of the extended Mittag-Leffler function in terms of the Laplace function.
Adnan Khan +3 more
doaj +1 more source