We design a numerical scheme for solving a Dynamic Programming equation with Malliavin weights arising from the time-discretization of backward stochastic differential equations with the integration ...

This paper offers a Bayesian framework for the calibration of financial models using neural stochastic differential equations ...

This article is an expository paper to demonstrate the usefulness of Pearson curves in density estimation especially for those unaware of this early development in statistics. It is shown how to fit ...

Check out this spice amplifier model. A basic Spice model that simulates an amplifier’s bandwidth, magnitude, phase, and transient response can be up and running in as little as three lines of code.

Fourier analysis and numerical methods have long played a pivotal role in the solution of differential equations across science and engineering. By decomposing complex functions into sums of ...

Brian Huge and Antoine Savine combine automatic adjoint differentiation with modern machine learning. In addition, they introduce general machinery for training fast, accurate pricing and risk ...