Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most challenging tasks in numerical ...

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 ...

I am performing structure optimization using Tidy3D's autograd integration, following a similar methodology to the "Inverse design optimization of a plasmonic nanoantenna metasurface" example notebook ...

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. In the quest to transform organizations, leaders often champion bold visions: compelling ...

This work presents the mathematical/theoretical framework of the “nth-Order Feature Adjoint Sensitivity Analysis Methodology for Response-Coupled Forward/Adjoint ...

Abstract: An adjoint-based shape optimization approach for the inverse design of microwave components is proposed. The proposed approach is a pure postprocessing process that only needs the field ...

Introduction: Regulatory agencies generate a vast amount of textual data in the review process. For example, drug labeling serves as a valuable resource for regulatory agencies, such as U.S. Food and ...

Liam Gaughan is a film and TV writer at Collider. He has been writing film reviews and news coverage for ten years. Between relentlessly adding new titles to his watchlist and attending as many ...