Numerical modeling and neural networks to identify model parameters from piezocone tests: II. Multi-parameter identification from piezocone data

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This paper presents a novel hybrid framework for generating and updating a synthetic population. We call it hybrid because it combines model-based and data-driven approaches. Existing generators produce a snapshot of synthetic data that becomes outdated ov ...

Numerical modeling and neural networks to identify model parameters from piezocone tests: II. Multi-parameter identification from piezocone data

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Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

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