Abstract: Deep learning models have shown great potential for fault location and classification tasks in distribution systems. Emerging multi-scale data sources such as waveform measurement units, ...

This repository contains the code and data used for the paper "Graph Neural Networks For Mapping Variables Between Programs", accepted at ECAI 2023. We present a novel graph program representation ...

Department of Computer Science, Metropolitan College, Boston University, Boston, MA, United States On the other hand, using MAD offers a direct measure of deviation and is more resilient to outliers.

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. The application presented here utilizes the R Shiny platform to ...

Abstract: Fiber-based quantum key distribution (QKD) systems are mature and commercialized, but their integration into existing optical networks is crucial for their widespread use, in particular in ...

Graph database vendor Neo4j Inc. is teaming up with Snowflake Inc. to make a library of Neo4j’s graph analytics functions available in the Snowflake cloud. The deal announced today allows users to ...

Quantum annealing (QA) can be competitive to classical algorithms in optimizing continuous-variable functions when running on appropriate hardware, show researchers from Tokyo Tech. By comparing the ...

Roll a die and ask students to identify the random variable. Since a die can only take on values of 1, 2, 3, 4, 5, or 6, this is a discrete random variable. Repeat ...