Researchers from the University of Maryland, Lawrence Livermore, Columbia and TogetherAI have developed a training technique that triples LLM inference speed without auxiliary models or infrastructure ...

Probability underpins AI, cryptography and statistics. However, as the philosopher Bertrand Russell said, "Probability is the most important concept in modern science, especially as nobody has the ...

Improving the conduct and reporting of newer methodological approaches Causal inference, the multidisciplinary field focused ...

Bayes' theorem is a statistical formula used to calculate conditional probability. Learn how it works, how to calculate it ...

Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies on multivariable models, which integrate ...

Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...

French AI darling Mistral is keeping the new releases coming this summer. Just days after announcing its own domestic AI-optimized cloud service Mistral Compute, the well-funded company has released ...

In the wake of the replication crisis, statistical power has become one of the central issues in debates about the quality of research. The widespread use of tests with low power is seen as a key ...

ABSTRACT: This study explores the application of Bayesian econometrics in policy evaluation through theoretical analysis. The research first reviews the theoretical foundations of Bayesian methods, ...

Abstract: The problem of statistical inference in its various forms has been the subject of decades-long extensive research. Most of the effort has been focused on characterizing the behavior as a ...