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.

Systematic reviews with network meta-analysis (NMA) have potential biases in their conduct, analysis, and interpretation. If the results or conclusions of an NMA are integrated into policy or practice ...

The Heisenberg uncertainty principle puts a limit on how precisely we can measure certain properties of quantum objects. But researchers may have found a way to bypass this limitation using a quantum ...

ABSTRACT: Machine learning (ML) has become an increasingly central component of high-energy physics (HEP), providing computational frameworks to address the growing complexity of theoretical ...

ABSTRACT: Machine learning (ML) has become an increasingly central component of high-energy physics (HEP), providing computational frameworks to address the growing complexity of theoretical ...

A fast and accurate surrogate model screens over 10,000 possible metal-oxide supports for a platinum nanocatalyst to prevent sintering under high temperatures. Metal nanoparticles catalyze reactions ...

3D rendering—the process of converting three-dimensional models into two-dimensional images—is a foundational technology in computer graphics, widely used across gaming, film, virtual reality, and ...

Abstract: The principal innovative contribution of this study resides in the introduction of a category of fractional delayed large-scale neural networks characterized by intricate topological ...

The applications of neural network models, shallow or deep, to information retrieval (IR) tasks falls under the purview of neural IR. Over the years, machine learning methods-including neural networks ...