Abstract: With the wide application of graph neural network (GNN) in many fields, how to extract and aggregate node features effectively has become a hot research issue. In this paper, we propose a ...

For Gabriel Petersson, the path to becoming a research scientist at OpenAI didn’t start in a lecture hall but began with a ...

Here are 11 free NPTEL data science and analytics courses from leading IITs cover graph theory, Bayesian modelling, Python, R ...

Overview: AI, data, finance, and digital skills are essential for high-demand jobs in 2025.Professional courses significantly enhance employability and career g ...

Two important architectures are Artificial Neural Networks and Long Short-Term Memory networks. LSTM networks are especially useful for financial applications because they are designed to work with ...

VIENTIANE – Vietnamese Minister of National Defence General Phan Văn Giang met with his Lao counterpart, Senior Lieutenant General Khamliang Outhakaysone, in Vientiane on Tuesday, during which they ...

Abstract: Recent advancements in deep neural networks heavily rely on large-scale labeled datasets. However, acquiring annotations for large datasets can be challenging due to annotation constraints.

TPUs are Google’s specialized ASICs built exclusively for accelerating tensor-heavy matrix multiplication used in deep learning models. TPUs use vast parallelism and matrix multiply units (MXUs) to ...