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Arxiv
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NOBLE -- Neural Operator with Biologically-informed Latent Embeddings to Capture Experimental Variability in Biological Neuron Models
- NOBLE is a neural operator framework introduced to capture experimental variability in biological neuron models.
- It learns a mapping from neuron features to the voltage response, predicting distributions of neural dynamics accounting for experimental variability.
- NOBLE offers models with dynamics consistent with observed responses and provides a $4200×$ speedup over numerical solvers.
- It enables efficient generation of synthetic neurons with trial-to-trial variability, contributing to a better understanding of brain function and neuroAI applications.
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