Rainfall prediction has advanced rapidly with the adoption of machine learning, but most models remain optimized for overall ...

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

This project implements state-of-the-art deep learning models for financial time series forecasting with a focus on uncertainty quantification. The system provides not just point predictions, but ...

Tumor Site–Specific Radiation-Induced Lymphocyte Depletion Models After Fractionated Radiotherapy: Considerations of Model Structure From an Aggregate Data Meta-Analysis Lymphocytes play critical ...

Training a machine learning model might sound tricky at first, but it’s actually pretty doable when you break it into steps. Whether you’re working with customer info, photos, or trying to predict ...

Abstract: Longitudinal and converted shear wave seismic data depict unique and abundant seismic response characteristics of gas reservoirs and help to elucidate the multicomponent seismic attributes ...

Gut bacteria are known to be a key factor in many health-related concerns. However, the number and variety of them is vast, as are the ways in which they interact with the body's chemistry and each ...

Incomplete data significantly hampers risk analysis for high-sea maritime accidents (HSMAs). This paper introduces a novel multi-source data-driven Bayesian network (DDBN) framework to address this ...

ABSTRACT: Missing data remains a persistent and pervasive challenge across a wide range of domains, significantly impacting data analysis pipelines, predictive modeling outcomes, and the reliability ...