Gaussian blue noise
… high-dimensional blue noise sets. Finally, we show an extension to adaptive sampling. …
It is also the gateway to highdimensional blue noise, as we will see in Section 5.2. There is …
It is also the gateway to highdimensional blue noise, as we will see in Section 5.2. There is …
[PDF][PDF] VoroSpokes Sampling for Bayesian Inference.
M Ebeida, N Winovich - 2019 - osti.gov
… To probe the interior of the polytope, radial distances {r,,} in the directions fc/),} can be
randomly sampled from appropriate distributions placed over the intervals {[O, Rp (0,)]}, …
randomly sampled from appropriate distributions placed over the intervals {[O, Rp (0,)]}, …
Higher-dimensional power diagrams for semi-discrete optimal transport
PC Caplan - arXiv preprint arXiv:2106.14730, 2021 - arxiv.org
… a blue noise sampling distribution is desirable to reduce aliasing effects that are produced
by a regular sampling … blue noise sampling distributions for rendering applications [10, 11]. …
by a regular sampling … blue noise sampling distributions for rendering applications [10, 11]. …
Rigorous Data Fusion for Computationally Expensive Simulations
… samples were also used in [36] to accurately calculate the volumes of unions of high dimensional
… We have also recently introduced the spoke-darts [37] blue-noise sampling technique …
… We have also recently introduced the spoke-darts [37] blue-noise sampling technique …
Voronoi density estimator for high-dimensional data: Computation, compactification and convergence
V Polianskii, GL Marchetti, A Kravberg… - Uncertainty in …, 2022 - proceedings.mlr.press
… In this section, we evaluate empirically the necessity of compactification for high-dimensional
data. To this end, we visually compare samples from the CVDE (with Gaussian kernel) and …
data. To this end, we visually compare samples from the CVDE (with Gaussian kernel) and …
Optimizing dyadic nets
… function for blue noise, and use it to generate nets with high-quality blue-noise frequency
power … of samples: (A) blue-noise sampling and (B) low-discrepancy (LD) sets and sequences. …
power … of samples: (A) blue-noise sampling and (B) low-discrepancy (LD) sets and sequences. …
Context-aware visual abstraction of crowded parallel coordinates
Z Zhou, Y Ma, Y Zhang, Y Liu, Y Liu, L Zhang, S Deng - Neurocomputing, 2021 - Elsevier
… So that, we design an adaptive blue noise sampling model to … task to sample data items
from high-dimensional space, … reduction method to project high-dimensional vectors into a 2D …
from high-dimensional space, … reduction method to project high-dimensional vectors into a 2D …
Semantic-aware visual abstraction of large-scale social media data with geo-tags
Z Zhou, X Zhang, X Zhou, Y Liu - IEEE Access, 2019 - ieeexplore.ieee.org
… blue noise sampling scheme to select a subset of original data in the vectorized space, and
optimize the sampled … Wei, ‘‘Spoke-darts for highdimensional blue-noise sampling,’’ ACM …
optimize the sampled … Wei, ‘‘Spoke-darts for highdimensional blue-noise sampling,’’ ACM …
Screen-space blue-noise diffusion of Monte Carlo sampling error via hierarchical ordering of pixels
… sampling error as a blue noise in screen space. We show that automatic diffusion of sampling
… such as Morton's Z-ordering, and assigning the samples to the pixels from successive sub-…
… such as Morton's Z-ordering, and assigning the samples to the pixels from successive sub-…
Novel Geometric Operations for Linear Programming
… efficiently sample Voronoi vertices (essentially finding nearest neighbors in high-dimensional …
The use of random spokes is another idea that we borrow from the Recursive Spoke Darts …
The use of random spokes is another idea that we borrow from the Recursive Spoke Darts …