The source code for the paper L. Lu, P. Jin, G. Pang, Z. Zhang, & G. E. Karniadakis. Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators. Nature Machine ...

Abstract: In the last decades many efficient methods have been proposed to generate waveforms with reduced aliasing, proving this field quite mature. However, the introduction of Antiderivative ...

Antidifferentiation is the reverse of differentiation. It is a fundamental concept in calculus and is essential in solving problems related to area, motion, and accumulation. Use this page to revise ...

Recall that an indefinite integral (or antiderivative) is so called as it provides a family of solutions with a constant term. It is called indefinite as the constant \(c\) can take any real value, ...

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We present a machine learning method based on random projections with Johnson-Lindenstrauss (JL) and/or Rahimi and Recht (2007) Random Fourier Features (RFFN) for efficiently learning linear and ...

Föllmer, Hans , and Alexander Schied. Stochastic Finance. An Introduction in Discrete Time. 5th revised and extended edition. 5th revised and extended editionth ed ...

The second part states that if a function is continuous, then it has an antiderivative, and the integral of the function can be computed using this antiderivative. Step-by-step examples illustrate how ...