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 ...

Abstract: Learning embeddings for entities and relations in knowledge graph (KG) have benefited many downstream tasks. In recent years, scoring functions, the crux of KG learning, have been human ...

einx is a Python library that provides a universal interface to formulate tensor operations in frameworks such as Numpy, PyTorch, Jax and Tensorflow. The design is based on the following principles: ...

A minimalistic and customizable graph card for Home Assistant Lovelace UI. The card works with entities from within the sensor & binary_sensor domain and displays the sensors current state as well as ...

Functions are one of the most fundamental concepts in mathematics, forming the foundation for topics in algebra, calculus and many other areas. A solid understanding of the basics of functions, ...

This section focuses on the key features and methods for working with linear graphs. It demonstrates how to sketch graphs from rules, derive rules from graphs, and calculate key features such as the ...

School of Automation and Electrical Engineering, Inner Mongolia University of Science and Technology, Baotou 014010, China Key Laboratory of Synthetical Automation for Process Industries at ...