Recent advancements in neural network methodologies have revolutionised hydrological forecasting, enabling more accurate, robust and computationally efficient predictions of water resource dynamics.

GRENOBLE, France – Dec. 7, 2023 – A team comprising CEA-Leti, CEA-List and two CNRS laboratories has published a paper in Nature Communications presenting what the authors said is the first complete ...

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, ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...