Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...

Abstract: Recent diffusion models provide a promising zero-shot solution to noisy linear inverse problems without retraining for specific inverse problems. In this paper, we reveal that recent methods ...

Many professors in the humanities are giving up on assigning papers. Working against the tsunami of AI writing is exhausting and disheartening. Those with heavy course loads can’t do it anymore. But ...

A variation of a puzzle called the “pick-up sticks problem” asks the following question: If I have some number of sticks with random lengths between 0 and 1, what are the chances that no three of ...

Abstract: Learning-based methods have been widely applied to solve electromagnetic (EM) inverse scattering problems (ISPs). In learning-based induced current inversions, the deterministic part of the ...

Bayesian statistics remain popular for addressing inverse problems, whereby quantities of interest are determined from their noisy and indirect observations. Bayes’ theorem forms the foundation of ...

I'm trying to solve an inverse problem to obtain two parameter values, a and b. I want the initial condition at time t=0 to fulfill a relation, e.g. x_t0 = a/b. Since I have to initialize a and b as ...