Key Takeaways Graph analytics reveals how data points connect, not just what they are, and is accessible without specialist skills or infrastructure. Zero-ETL means faster insight without moving ...

Domain adaptation aims to deal with learning problems in which the labeled training data and unlabeled testing data are differently distributed. Maximum mean discrepancy (MMD), as a distribution ...

Aggregate to Adapt: Node-Centric Aggregation for Multi-Source-Free Graph Domain Adaptation (WWW-2025). This is a PyTorch implementation of the GraphATA algorithm, which tries to address the ...

In this paper, we address the problem of improving time-series classification performance in graph environments. With the recent increase in graph analytics, many studies analyzing time-series within ...

Knowledge graphs—machine-readable data representations that mimic human knowledge—are bridging the gap between proprietary enterprise data and safe, reliable, helpful LLMs.

Understand the building blocks of knowledge graphs – entities, relationships and attributes – and how they relate to information retrieval.

Over the past year, Consumer Reports sought to answer this question by conducting seasonal testing on popular, new EVs: Ford Mustang Mach-E, Hyundai Ioniq 5, Tesla Model Y, and Volkswagen ID.4.

To find the range of radical functions, examine their graphs. The range will consist of all y-values for which there’s a corresponding x-value on the graph. 5. Exponential and logarithmic functions: ...

Ukraine’s real problem, in four graphs By Marcela Escobari Globe Correspondent,June 8, 2014, 12:17 a.m.