Conditional diffusion models sample viable parameter manifolds whose geometry quantifies compensation, degeneracy, and effective constraints in Lorenz, Izhikevich, and reduced spiking-network models.
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Prinz, Dirk Bucher, and Eve Marder
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Diffusion learning reveals viable parameter manifolds and compensation geometry in biological dynamical systems
Conditional diffusion models sample viable parameter manifolds whose geometry quantifies compensation, degeneracy, and effective constraints in Lorenz, Izhikevich, and reduced spiking-network models.