Inverse spectral problems for integro-differential operators address the challenge of reconstructing the underlying operator – often comprising both differential and integral components – from its ...

Geometric Neural Operators (GNPs) allow for data-driven deep learning of features from point-cloud representations and other datasets for tasks involving geometry. This includes training protocols and ...

Researchers have made a breakthrough in the ability to solve engineering problems. In a new paper published in Nature entitled, “A scalable framework for learning the geometry-dependent solution ...

The key is the word “differential” and understanding that investors, operators and advisors need different strengths. The best investors can almost see into the future. The best operators build ...

Every owner-operator knows today's trucking business environment is challenging, at best. Between global forces pulling on demand for goods and diesel, and a glut of trucking capacity outpacing demand ...

Abstract: The current investigation introduces a fresh category of analytic functions by utilizing the differential operator referred to as the q-Shaba operator. Termed as the q-Shaba differential ...

The remarkable potentials of Artificial Intelligence (AI) and Deep Learning have paved the way for a variety of fields ranging from computer vision and language modeling to healthcare, biology, and ...

When one function is defined as a differential operation on another function, it’s often desirable to invert the definition, to effectively “undo” the differentiation. A Green’s function approach is ...

School of Geosciences, China University of Petroleum (East China), Qingdao, China The accurate simulation of anisotropic media is critical in seismic imaging and inversion. In recent years, some ...

Modeling complex physical dynamics is a fundamental task in science and engineering. Traditional physics-based models are first-principled, explainable, and sample-efficient. However, they often rely ...

Abstract: Here we present a new approach for the design of open-loop control or motion planning for partial differential equations (PDE) and systems. It is based on pseudo-differential operator (/spl ...