Abstract: We proposed an optimisation algorithm based on the sequence-to-sequence (Seq2Seq) stacking of the gate recurrent unit (GRU) model to characterise and approximate the forward problem of ...
Harry Wilson (left) and Piero Hincapie, two players who can give your FPL team an edge Getty Images The run-up to Christmas is famously chaotic in Fantasy Premier League. Matches come thick and fast, ...
Researchers have made a breakthrough in the ability to solve engineering problems. In a new paper published in Nature entitled, “A scalable framework for learning the geometry-dependent solution ...
ABSTRACT: Accurately approximating higher order derivatives is an inherently difficult problem. It is shown that a random variable shape parameter strategy can improve the accuracy of approximating ...
Differential equations are equations that involve an unknown function and its derivatives with respect to one or more independent variables. They play a fundamental role in various fields of science, ...
For the numerical comparisons of the methods, we examine their convergence rates for approximating the surface gradient, divergence, and Laplacian as the point clouds are refined for various parameter ...
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.
In this paper, we presented an asymptotic fitted approach to solve singularly perturbed delay differential equations of second order with left and right boundary. In this approach, the singularly ...
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