Essentially all cells in an organism's body have the same genetic blueprint, or genome, but the set of genes that are ...

Finite basis physics-informed neural networks (FBPINNs) This repository allows you to solve forward and inverse problems related to partial differential equations (PDEs) using finite basis ...

The proof, known to be so hard that a mathematician once offered 10 martinis to whoever could figure it out, connects quantum ...

Federated Scientific Machine Learning for Approximating Functions and Solving Differential Equations With Data Heterogeneity By leveraging neural networks, the emerging field of scientific machine ...

A new definition of a guiding function for functional differential equations is given, which is sometimes better for applications than the known one by Mawhin. We then prove an existence result for ...

Neural operators are a class of neural networks to learn mappings between infinite-dimensional function spaces, and recent studies have shown that using neural operators to solve partial differential ...

Mathematicians have devised a new way to solve higher-order polynomial equations, ushering in a 'dramatic revision of a basic chapter in algebra'.

A partial differential operator together with functions [Source: Nature] Researchers have made a breakthrough in the ability to solve engineering problems. In a new paper published in Nature entitled, ...

Waveguide-based structures can solve partial differential equations by mimicking elements in standard electronic circuits. This novel approach, developed by researchers at Newcastle University in the ...