5 papers indexed here
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
A novel method for nonparametric density estimation from weighted samples is proposed, represented in discretized form as a regular grid of square roots of probabilities or density values, and achieves smoothness with an additional Fisher Information regularization.
A Predictor–Corrector Gaussian Homotopy (PCGH) method is proposed that formulates Gaussian homotopy optimization as a path tracking problem, and geometry-aware arc-length parameterizations based on Fisher-information and Hessian-derived metrics are introduced for efficient approximation of the Gaussian convolution and...
DENSE is an ensemble of multi layer perceptrons (MLPs) that is trained to minimize a modified Cram´er–von Mises distance in the joint space of inputs and outputs that enables non-parametric representations of arbitrary densities without (complex) likelihood design.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
