Abstract: Graph Convolutional Networks (GCNs) have been widely studied for attribute graph data learning. In many applications, graph node attributes/features may contain various kinds of noises, such ...

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Pypst helps you dynamically generate Typst code directly in Python. No manual string manipulation required. It has two major use cases: Generating full Typst documents to be rendered as PDFs ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

Can the users of financial statements and annual reports rely upon the charts in them for accuracy? A sample of 50 public companies’ yearly reports collected by the author found that 86% had at least ...

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...

Rajiv Shesh is the Chief Revenue Officer at HCLSoftware where he leads revenue growth & customer advocacy for Products & Platforms division. What’s really powering AI? High-quality data—foundational ...

The Canadian Securities Administrators (CSA) will implement amended derivatives trade reporting rules on July 25, 2025, bringing improvements that also come with considerable implementation demands.