The financial crime compliance industry has spent two decades building better detection. Transaction monitoring rules have ...

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 crypto market is currently at a fever pitch as investors scramble to secure positions in projects that define the 2026 ...

Payments infrastructure is not a static system. It is a living network of interdependencies — between liquidity pools, ...

The term evidence-based medicine, coined by Dr. Guyatt in 1991 (1), describes the practice of medicine rooted in the best available scientific evidence (2). Since its inception, evidence-based ...

Evidence-based Directed Acyclic Graphs (DAGs) are effective tools to comprehensively visualize complex causal and biasing pathways in pharmacoepidemiologic research in rheumatology. This paper ...

Abstract: Subcircuit boundary prediction is an important application of machine learning in logical analysis, effectively supporting tasks such as functional verification and logic optimization.

The project implements a Directed Acyclic Graph (DAG) executor in Python that enables the creation and execution of computational pipelines. It handles the dependencies between tasks (represented as ...

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 ...

The Perspective by Tiwary et al. (8) offers a comprehensive overview of generative AI methods in computational chemistry. Approaches that generate new outputs (e.g., inferring phase transitions) by ...