A multi-scale extension of the Fisher information metric, derived from coarse-graining contraction rules, exactly captures the structure of mutual information in neural population codes and can be estimated via diffusion models.
Generalized shape metrics on neural representations.Advances in Neural Information Processing Systems, 34:4738–4750
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A multi-scale information geometry reveals the structure of mutual information in neural populations
A multi-scale extension of the Fisher information metric, derived from coarse-graining contraction rules, exactly captures the structure of mutual information in neural population codes and can be estimated via diffusion models.