Abstract: This paper provides an updated overview of recent literature on stock market prediction using machine learning methods. Neural network-based models, particularly those focused on predicting ...

Machine learning techniques that make use of tensor networks could manipulate data more efficiently and help open the black ...

In this paper, we introduce R-NET, an end-to-end neural networks model for reading comprehension style question answering, which aims to answer questions from a given passage. We first match the ...

The work that we’re doing brings AI closer to human thinking,” said Mick Bonner, who teaches cognitive science at Hopkins.

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, ...

Felimban, R. (2025) Financial Prediction Models in Banks: Combining Statistical Approaches and Machine Learning Algorithms.

AMD has been steadily expanding its FidelityFX Super Resolution technology since 2021, but “Redstone” represents the biggest ...

Abstract: Assessing the failure of urban gas pipelines is crucial for identifying risk factors and preventing gas accidents that result in economic losses and casualties. Most previous studies on gas ...

The human mind is turning out to be far stranger and more intricate than the tidy diagrams in old biology textbooks ever ...