The hype surrounding machine learning, a form of artificial intelligence, can make it seem like it is only a matter of time ...

The hype surrounding machine learning, a form of artificial intelligence, can make it seem like it is only a matter of time ...

A new article notes that journal articles reporting how well machine learning models solve certain kinds of equations are often overly optimistic. The researchers suggest two rules for reporting ...

An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and ...

The reason why it was able to accurately say "Paris" instead of, lets say, "New York" is due to a combination of its ...

We propose a novel machine learning architecture, termed model-integrated neural networks (MINN), that can learn the physics-based dynamics of general autonomous or non-autonomous systems consisting ...

Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential ...

Filipović, Damir and Tappe, Stefan 2007. Existence of Lévy term structure models. Finance and Stochastics, Vol. 12, Issue. 1, p. 83.

Compaan, E. and Tzirakis, N. 2017. Well-posedness and nonlinear smoothing for the “good” Boussinesq equation on the half-line. Journal of Differential Equations ...

For the PV converter differential equations to capture instantaneous current and voltage, they derived, with maximum power point operation as a critical focus. Similarly, the researchers established ...