Science

A new framework uses simulated shopping experiences to train artificial intelligence agents to conduct more effective product research online.

A new approach leverages the power of Random Forests to transform tabular data into graph representations, unlocking enhanced performance with Graph Neural Networks.

New research reveals that while machine learning excels at classifying polynomial roots, it doesn’t automatically unlock the underlying mathematical principles.

New research reveals how user choice within multi-learner systems can inadvertently lead to overspecialization and diminished overall learning outcomes.

A new approach uses artificial intelligence to analyze news and media for financial crime risks, going beyond simple keyword matching.

Researchers have unveiled TradeFM, a large-scale generative model capable of learning and replicating the complex dynamics of financial markets from vast transaction data.

A new framework improves the ability of AI to understand complex questions about time series data by connecting visual patterns with natural language semantics.

New research reveals that transformer networks develop consistent internal representations of state even when trained on variations of a single task, opening doors to predictable behavior and causal interventions.

Researchers have demonstrated that artificial intelligence can learn to dynamically adjust the parameters of optimization algorithms, leading to improved performance on complex problem landscapes.

A new object detection model, Association DETR, significantly improves performance by intelligently incorporating background context into its analysis.