The Poisson distribution is widely used in artificial intelligence (AI) and machine learning. In Bayesian inference, probability distributions often help solve problems that would otherwise be ...

Explore how probability distribution functions are integral in training and evaluating machine learning models for accurate predictions and insights.

Probability density function (PDF) estimation is a constantly important topic in the fields related to artificial intelligence and machine learning. This paper is dedicated to considering problems on ...

Abstract: We present a theoretical framework of probabilistic learning derived from the maximum probability (MP) theorem shown in this article. In this probabilistic framework, a model is defined as ...

Latest Machine Learning Research at MIT Presents a Novel "Poisson Flow" Generative Model (PFGM) That Maps any Data Distribution into a Uniform Distribution on a High-Dimensional Hemisphere ...

Water molecules at the ligand–protein interfaces play crucial roles in the binding of the ligands, but the behavior of protein-bound water is largely ignored in many currently used machine learning ...

Conclusion: Machine learning can identify patterns of diastolic function that better stratify the risk for decompensation than the current consensus recommendations in HF. Integrating this data-driven ...

The mean, variance and probability distribution function are commonly obtained from PPF calculations. However, the conventional PPF calculation results cannot be used to directly solve many actual ...