Learn how to solve linear systems using the matrix approach in Python. This video explains how matrices represent systems of equations and demonstrates practical solutions using linear algebra ...

Abstract: Generalized power iteration-based precoding (GPIP) exhibits superior performance in maximizing spectral efficiency for multi-antenna communications. Increasing the number of antennas, ...

It’s happened to all of us: you find the perfect model for your needs — a bracket, a box, a cable clip, but it only comes in STL, and doesn’t quite fit. That problem will never happen if you’re using ...

Abstract: The acquisition of attitude, velocity, and position is an essential task in inertial navigation, achieved by integrating inertial sensor measurements. Recently, the functional iteration ...

Kwangjun Ahn, Senior Researcher at Microsoft Research AI Frontiers, introduces Dion, a next-generation optimizer in the style of Muon that orthonormalizes only the top-r subspace via amortized power ...

Use it to promote divergent thinking. by Tojin T. Eapen, Daniel J. Finkenstadt, Josh Folk and Lokesh Venkataswamy There is tremendous apprehension about the potential of generative AI—technologies ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using the Newton iteration algorithm. Compared to other algorithms, Newton ...

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 difficult tasks in numerical ...

The Nature Index 2025 Research Leaders — previously known as Annual Tables — reveal the leading institutions and countries/territories in the natural and health sciences, according to their output in ...

Discover how nvmath-python leverages NVIDIA CUDA-X math libraries for high-performance matrix operations, optimizing deep learning tasks with epilog fusion, as detailed by Szymon Karpiński.