Amid the chaos of revolutionary France, one man’s mathematical obsession gave way to a calculation that now underpins much of ...

In 540p-to-1080p comparisons, NSS improves stability and detail retention. It performs well in scenes with fast motion, ...

Government procurement contracts can be complicated, with extensive risk analysis and compliance reviews. The traditional methods of contract analytics are time-consuming and often inexact, thus ...

Abstract: The recent success of graph neural networks (GNNs) in the area of pattern recognition (PR) has increased the interest of researchers to use these frameworks in non-euclidean structures. This ...

Abstract: Many graph-based algorithms in high performance computing (HPC) use approximate solutions due to having algorithms that are computationally expensive or serial in nature. Neural acceleration ...

This project demonstrates how to use a machine learning model, specifically a feedforward neural network implemented with TensorFlow/Keras, to learn the mathematical transformation from the sine ...

The HNSW algorithm is an efficient and scalable method for approximate nearest neighbor search in high-dimensional spaces. This Golang library provides a generic implementation of the HNSW algorithm, ...

Scientists discovered that a gut bacteria molecule called corisin can travel to the kidneys, triggering inflammation and ...

Though the line may be packed with wardrobe staples, the garments themselves are anything but basic. Instead, elevated pieces ...

I co-created Graph Neural Networks while at Stanford. I recognized early on that this technology was incredibly powerful. Every data point, every observation, every piece of knowledge doesn’t exist in ...