The introduction of dynamic arrays triggered the biggest change to how we work with Microsoft Excel formulas in years, if not decades. They allow a single formula to spill multiple results into ...

NVIDIA releases detailed cuTile Python tutorial for Blackwell GPUs, demonstrating matrix multiplication achieving over 90% of cuBLAS performance with simplified code. NVIDIA has published a ...

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 ...

Abstract: The random matrix model provides a straightforward and low-complexity algorithm, making it a promising solution for extended target tracking and shape estimation. However, the random matrix ...

Explore the "frp_rl" repository to discover the Free Random Projection technique for in-context reinforcement learning. This project offers a JAX-based implementation that helps agents adapt and learn ...

According to mathematical legend, Peter Sarnak and Noga Alon made a bet about optimal graphs in the late 1980s. They’ve now both been proved wrong. It started with a bet. In the late 1980s, at a ...

We know why you’re here, reader. We know what you’ve been doing. We know why you hardly sleep, why you live alone, and why, night after night, you sit at your computer. We know because we were once ...

ABSTRACT: Properties from random matrix theory allow us to uncover naturally embedded signals from different data sets. While there are many parameters that can be changed, including the probability ...

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.

Properties from random matrix theory allow us to uncover naturally embedded signals from different data sets. While there are many parameters that can be changed, including the probability ...