A magnitude 7.5 earthquake struck 28 km southeast of Yumare, Venezuela, on June 24, 2026, and within minutes the U.S.

Abstract: This paper proposes a direct model for conditional probability density forecasting of residential loads, based on a deep mixture network. Probabilistic residential load forecasting can ...

Thomas J Catalano is a CFP and Registered Investment Adviser with the state of South Carolina, where he launched his own financial advisory firm in 2018. Thomas' experience gives him expertise in a ...

If a new pathogen causes a large epidemic, then it might “burn out” before causing a second epidemic. The burnout probability can be estimated from large numbers of computationally intensive ...

Reliable earthquake recurrence probability assessment is crucial for seismic hazard mitigation but remains challenging due to sparse paleoseismic data on individual faults. We present an enhanced ...

Conditional Flow Matching (CFM) is a fast way to train continuous normalizing flow (CNF) models. CFM is a simulation-free training objective for continuous normalizing flows that allows conditional ...

The binomial distribution is a key concept in probability that models situations where you repeat the same experiment several times, and each time there are only two possible outcomes—success or ...

Probability provides a robust framework to understand uncertainty, assess risks, and make informed decisions. From predicting customer behavior to managing supply chain disruptions, it plays a vital ...

A long-standing challenge in statistical mechanics has been to quantify the nonequilibrium nature of active systems such as swarming bacteria, schooling fish, and flocking birds. The entropy ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. As a supervised machine learning algorithm, conditional random fields are mainly used ...

Abstract: This paper proposes a direct model for conditional probability density forecasting of residential loads, based on a deep mixture network. Probabilistic residential load forecasting can ...