For making probabilistic inferences, a graph is worth a thousand words. A Bayesian network is a graph in which nodes represent entities such as molecules or genes. Nodes that interact are connected by ...
A new technical paper titled “Bringing uncertainty quantification to the extreme-edge with memristor-based Bayesian neural networks” was published by researchers at Université Grenoble Alpes, CEA, ...
ABSTRACT. Stakeholder participation is becoming increasingly important in water resources management. In participatory processes, stakeholders contribute by putting forward their own perspective, and ...
On September 27th, 2024, the Department of Mathematics and Statistics at Concordia University proudly hosted the 11th installment of the Professor T.D. Dwivedi Memorial Lecture series. This annual ...
A novel Bayesian Hierarchical Network Model (BHNM) is designed for ensemble predictions of daily river stage, leveraging the spatial interdependence of river networks and hydrometeorological variables ...
On Friday the 11th of November 2022, PhD, M.Sc. Laura Uusitalo defends her PhD thesis on Bayesian network modelling of complex systems with sparse data: Ecological case studies. The thesis is related ...
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