Probability distributions are fundamental tools in statistics and data science, allowing us to model the likelihood of different outcomes in a random event. While we often work with complete and ...

Probability theory is indispensable in computer science: It is at the core of artificial intelligence and machine learning, which require decision making under uncertainty. It is integral to CS theory ...

Sampling from probability distributions with known density functions (up to normalization) is a fundamental challenge across various scientific domains. From Bayesian uncertainty quantification to ...

Abstract: While probability distribution functions are crucial for simulating random processes, research on these functions and their features is required. However, studies have demonstrated that in ...

1 Hainan Power Transmission and Transformation Maintenance Branch of Hainan Power Grid Co., Ltd., Haikou, China 2 College of Electrical and Information Engineering, Changsha University of Science and ...

Probability distribution is an essential concept in statistics, helping us understand the likelihood of different outcomes in a random experiment. Whether you’re a student, researcher, or professional ...

In the field of statistics and probability, marginal distribution plays a critical role in understanding the behavior of variables. It is a method used to determine the probability distribution of a ...

Imagine a scenario where a team of doctors faces a perplexing medical puzzle. A patient shows a range of symptoms, each pointing to multiple possible diseases. How can they navigate this diagnostic ...

Joint Probability Trees (short JPTs) are a formalism for learning of and reasoning about joint probability distributions, which is tractable for practical applications. JPTs support both symbolic and ...