GeoAI '24: Proceedings of the 7th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery This study addresses the challenges inherent in building use type classification, ...

The package needs these Python modules to be installed beforehand. pywt, install using: "conda install pywavelets" prox_tv, install using: "pip install prox_tv" Other commonly used Python packages: ...

Study Rundown: MGUS may be a precursor to MM and other lymphoproliferative disorders. The way to distinguish between SMM and MGUS is by looking at the bone marrow plasma cells (BMPC). They are ...

Abstract: Data-driven approaches have been widely used in the field of traction system and equipment fault diagnosis. However, limited training samples can cause data-driven models to face the dilemma ...

Here’s why we appear to be getting cooler, and what that could mean when it comes to fevers. By Dana G. Smith Over the past few decades, evidence has been mounting that the average human body ...

Abstract: We propose a fast method for deterministic multi-variate Gaussian sampling. In many application scenarios, the commonly used stochastic Gaussian sampling could simply be replaced by our ...

Probabilistic Deep Learning finds its application in autonomous vehicles and medical diagnoses. This is an increasingly important area of deep learning that aims to quantify the noise and uncertainty ...

Studies of resting state functional MRI (rs-fRMI) are increasingly focused on “dynamics”, or on those properties of brain activation that manifest and vary on timescales shorter than the scan's full ...

In the social and behavioral sciences, it is recommended that effect sizes and their sampling variances be reported. Formulas for common effect sizes such as standardized and raw mean differences, ...

This paper develops a parameter-expanded Monte Carlo EM (PX-MCEM) algorithm to perform maximum likelihood estimation in a multivariate sample selection model. In contrast to the current methods of ...