Sticking with the same people might feel safe and comfortable. But a new Northwestern University study suggests it can ...

Scientists say they've made a key breakthrough that would allow robots to figure out complex tasks on their own, but experts ...

From smarter hypothesis testing with e-values to AI systems that model emotions, Bayesian methods and probabilistic reasoning are transforming how machines—and humans—make decisions under uncertainty.

The ability to make adaptive decisions in uncertain environments is a fundamental characteristic of biological intelligence. Historically, computational ...

Identification of each animal in a collective becomes possible even when individuals are never all visible simultaneously, enabling faster and more accurate analysis of collective behavior.

Accurate disaster prediction combined with reliable uncertainty quantification is crucial for timely and effective decision-making in emergency management. However, traditional deep learning methods ...

Abstract: Bayesian networks are widely used for causal discovery and probabilistic modeling across diverse domains including healthcare, multi-dimensional data analysis, environmental modeling, and ...

ABSTRACT: The present study aimed to examine the impact of emotion regulation on depression symptoms, with a particular focus on the mediating roles of social anxiety and loneliness among Chinese ...