MM-SOLD is a training-free particle sampler whose large-particle limit converges to a moment-matched Gibbs distribution obtained by exponentially tilting a score-smoothed target.
Chikuse.Statistics on Special Manifolds
6 Pith papers cite this work. Polarity classification is still indexing.
6
Pith papers citing it
representative citing papers
MSFAST extends the FAST FPCA method to multivariate sparse data via Bayesian modeling with orthonormal splines, standardization, Procrustes alignment, and efficient computation, yielding valid inferences especially in low signal-to-noise settings.
Derives deterministic MMD, KSD, and KL objectives with rotationally invariant kernels on the hypersphere, yielding more stable SSL training and dataset-dependent geometry in learned representations.
A nonmonotone subgradient algorithm is developed for upper-C^2 optimization on submanifolds with stationarity and KL-based convergence guarantees.
No additional conditions beyond the spline projection and mixed-effects equivalence are needed for the smoothing prior and posterior to be proper in fully-Bayesian FPCA.