3 days ago · This paper is about AdaOpt, a probabilistic multivariable optimization model for statistical/machine learning classification. View full-text. Presentation.

6 days ago · Proper scoring rules are an essential tool to assess the predictive performance of probabilistic forecasts. However, propriety alone does not ensure an ...

4 days ago · The study introduces a novel probabilistic approach to identify and reduce the influence of noisy data in machine learning datasets.

3 days ago · Our scope is to perform forecasting on unseen time series using a forecasting model trained on a different data source without the need for retraining or ...

5 days ago · The fundamental need to produce accurate point and distributional forecasts across various horizons presents significant challenges to existing forecasting ...

4 days ago · PP is a novel programming paradigm developed in the area of Probabilistic Machine Learning that defines models of random variables in general-purpose ...

4 hours ago · Machine learning (ML) can improve the accuracy of weather forecasts by providing data-driven models that are highly competitive with traditional numerical ...

2 days ago · We aim to develop world-beating forecasting models using advanced Artificial Intelligence (AI) within a specialist research project. RWE AI Research Laboratory.

6 days ago · This work developed a probabilistic methodology based on ensemble simulations that incorporated uncertainty in weather, fuel loading, and model physics ...

4 days ago · Forecasting demand for new product introductions by using AWS machine learning services ... A probabilistic, memory-efficient data structure that is used ...