A new technical paper titled “Massively parallel and universal approximation of nonlinear functions using diffractive ...

Abstract: Network function computation is investigated in the letter. In the model, a target function, of which the inputs are generated at multiple source nodes, is ...

Abstract: In this paper, we give an efficient method for constructing a large set of disjoint spectra functions without linear structures, which are not equivalent to partially linear functions. This ...

The Linear MCP currently returns all issues including completed ones when using list_issues or list_my_issues, which can bloat context unnecessarily when working with AI assistants. When calling the ...

Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...

Learn what is Linear Regression Cost Function in Machine Learning and how it is used. Linear Regression Cost function in Machine Learning is "error" representation between actual value and model ...

Students come to Bethel with a variety of backgrounds and histories in math that may have included previous work in algebra, precalculus, or calculus. Success in Bethel’s Precalculus and Calculus 1 ...

The use of Linear Complementarity Problems (LCP) is a powerful method for modeling switched systems, particularly in the context of power electronic circuits. Switched circuits are ubiquitous in ...

Can you chip in? This year we’ve reached an extraordinary milestone: 1 trillion web pages preserved on the Wayback Machine. This makes us the largest public repository of internet history ever ...

A linear demand curve is a line representing the relationship between the demand for a product or service and its price. Everyone knows that sales are proportional to price: The more you charge for an ...