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Flow Surrogate of Computer Models

Manifold Surrogate of Computer Models

For computer models of complex physical and engineering systems, surrogates are often necessary to accelerate analyses that require large numbers of model evaluations. When a computer model is stochastic, its surrogate should also be stochastic. …

Accelerated Subspace-constrained Mean Shift

Subspace-constrained Mean Shift (SCMS) is an iterative algorithm for non-parametric ridge estimation. Although SCMS is computationally feasible, it is only linearly convergent and its computational complexity per iteration is quadratic in sample size …

Manifold Scaffold Sampling

When data points exhibit salient geometric structure, density estimation and generative modeling can be more efficient by exploiting the data manifold. Here we propose Manifold Scaffold, a generative model for data concentrated near a manifold. First …

Kernel Density Estimation and Sampling on Riemmanian Submanifolds

For probability density estimation on Riemannian manifolds, many methods have been proposed, parametric or non-parametric. However, whether they can be implemented for general manifolds is in question. Here we propose a kernel-based method for …