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cs.LG2023★ 1 cited
Implicit Gaussian process representation of vector fields over arbitrary latent manifolds
Robert L. Peach, Matteo Vinao-Carl, Nir Grossman +6
Gaussian processes (GPs) are popular nonparametric statistical models for learning unknown functions and quantifying the spatiotemporal uncertainty in data. Recent works have exten…
cs.LG2023★ 25 cited
Interpretable statistical representations of neural population dynamics and geometry
Adam Gosztolai, Robert L. Peach, Alexis Arnaudon +2
The dynamics of neuron populations commonly evolve on low-dimensional manifolds. Thus, we need methods that learn the dynamical processes over neural manifolds to infer interpretab…