Before the term artificial intelligence was coined in 1955, there were glimmers of AI’s potential in folklore, fiction, and the early engineering feats of the 19th and early 20th centuries. These ...

The mathematics behind artificial intelligence (AI) and machine learning (ML) rely on linear algebra, calculus, probability, ...

However, they have shortcomings in extracting meaningful spatial and temporal relationships. We propose a supervised data-driven method to predict S-wave velocity using a graph convolutional network ...

which will seriously degrade the network performance. To solve this problem, a key node identification model based on Graph Convolutional Networks (GCN), named KNIGCN, is proposed. Specifically, the ...

GraphPro is a versatile and pluggable OO python library designed for leveraging deep graph learning representations to gain insights into structural proteins and ...

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical ...

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