ABSTRACT: This paper introduces a methodology that enables the relational learning framework to incorporate quantitative data derived from experimental studies in microbial ecology. The focus of using ...
Graph Neural Network directly constructed from the Bottom-Clause generated by Inductive Logic Programming (ILP). The resulting GNN models are to be known as "BotGNNs" (singular, "BotGNN"). The present ...
Inductive Logic Programming (ILP) is a form of Machine Learning. The goal of ILP is to induce a hypothesis, as a set of logical rules, that generalises training examples. This project is intended to ...
Abstract: Despite recent advances in modern machine learning algorithms, the opaqueness of their underlying mechanisms continues to be an obstacle in adoption. To instill confidence and trust in ...
Google has introduced Mangle, a new open-source programming language that extends the classic logic-based language Datalog for modern deductive database programming. Implemented as a Go library, ...
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JavaScript’s arrays can hold heterogeneous types, change size on the fly, and readily insert or remove elements. Traditional methods like slice, splice, and push/pop do this by operating on the array ...
There are various approaches to developing programmable logic controller (PLC) applications using experimental techniques. Modifying existing PLC ladder logic programs is another common approach ...
This past spring, the Henderson-Hopkins School found itself with an extra 85 students on campus: Twice a week, 55 undergraduate and 30 graduate students from Johns Hopkins University would travel to ...
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