Abstract: Assessing the failure of urban gas pipelines is crucial for identifying risk factors and preventing gas accidents that result in economic losses and casualties. Most previous studies on gas ...

Here are 11 free NPTEL data science and analytics courses from leading IITs cover graph theory, Bayesian modelling, Python, R, databases and big-data stats. These are all free to audit, and enrolment ...

Objective: Based on the Bayesian network, this study investigates the impact pathways of multidimensional factors related to the living environment—specifically housing factors, exposure to daily ...

In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...

Introduction: During the commissioning and operation of shale gas pipelines, multiple perforation accidents caused by internal corrosion have occurred. Research on internal corrosion probability ...

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...

Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...

This webinar introduces healthcare researchers to Bayesian meta-analysis methods, challenging the perception that these methods are inaccessible to non-statistical researchers. The session ...

SensibleSleep is an open-source Python package that implements a Hierarchical Bayesian model for learning sleep patterns from smartphone screen-on events.