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Found 4 papers, 2 papers with code
Multi-Modal Learning-based Reconstruction of High-Resolution Spatial Wind Speed Fields
We show that in-situ observations with richer temporal resolution represent an added value in terms of the model reconstruction performance.
Learning-based estimation of in-situ wind speed from underwater acoustics
As sea surface winds produce sounds that propagate underwater, underwater acoustics recordings can also deliver fine-grained wind-related information.
A developmental approach for training deep belief networks
Deep belief networks (DBNs) are stochastic neural networks that can extract rich internal representations of the environment from the sensory data.
Emergence of Network Motifs in Deep Neural Networks
Network science can offer fundamental insights into the structural and functional properties of complex systems.
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