Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using ...

Implementations of matrix multiplication via diffusion and reactions, thus eliminating the need for electronics, have been proposed as a stepping stone to realize molecular nano-neural networks (M3N).

Coded computing has proved its efficiency in handling a straggler issue in distributed computing framework. However, in a coded distributed computing framework, there may exist Byzantine workers who ...

To our knowledge, this is the first algorithm which combines fast matrix multiplication with hashing for the light bulb problem or any closest pair problem, and it leads to faster algorithms for small ...

in this file, i implemented llama3 from scratch, one tensor and matrix multiplication at a time. also, im going to load tensors directly from the model file that meta provided for llama3, you need to ...

Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math ...

The Kronecker product of matrices plays a central role in mathematics and in applications found in engineering and theoretical physics. These applications are signal processing, statistical physics, ...

This book examines the issues across the breadth of elasticity theory. Firstly, the underpinning mathematics of vectors and matrices is covered. Thereafter, the equivalence between the inidicial, ...