Compact representation of graph data is a fundamental problem in pattern recognition and machine learning area. Recently, graph neural networks (GNNs) have been widely studied for graph-structured ...

Subsequently, a GIN-based model for graph representation learning is employed to extract features necessary for ship type recognition. The model’s performance is evaluated through experiments on ...

Hiroto Nagai, a geoenvironmental scientist and associate professor at Rissho University in Tokyo, compiled publicly available climate data from the Arctic and Antarctic to produce a 6-minute ...

This repository contains a Python implementation for solving ordinary differential equations (ODEs) using various numerical methods, including the Euler method, Heun's method, the Midpoint method, and ...

Data visualization is a crucial aspect of data analysis, as it allows us to see patterns, trends, and outliers that might not be immediately apparent in raw data. By transforming data into visual ...

Advances in Chemical Representations and AI in Drug Discovery: The past century’s technological advancements, especially the computer revolution and high-throughput screening in drug discovery, have ...

This data analysis includes, for example, sampling, computing summary statistics, and creating visual representation of data via basic charts. Data analytics typically includes more sophisticated ...

The accounting press has heralded the growing and transformational use of data analytics in accounting—auditing in particular. A recent poll regarding top priorities for audit leaders conducted by ...