Zobrazeno 1 - 10
of 224
pro vyhledávání: '"Peterka, Tom"'
Functional approximation as a high-order continuous representation provides a more accurate value and gradient query compared to the traditional discrete volume representation. Volume visualization directly rendered from functional approximation gene
Externí odkaz:
http://arxiv.org/abs/2409.00184
Advances in high-performance computing require new ways to represent large-scale scientific data to support data storage, data transfers, and data analysis within scientific workflows. Multivariate functional approximation (MFA) has recently emerged
Externí odkaz:
http://arxiv.org/abs/2408.13193
Feature grid Scene Representation Networks (SRNs) have been applied to scientific data as compact functional surrogates for analysis and visualization. As SRNs are black-box lossy data representations, assessing the prediction quality is critical for
Externí odkaz:
http://arxiv.org/abs/2407.19082
In situ approaches can accelerate the pace of scientific discoveries by allowing scientists to perform data analysis at simulation time. Current in situ workflow systems, however, face challenges in handling the growing complexity and diverse computa
Externí odkaz:
http://arxiv.org/abs/2404.03591
Considering the challenges posed by the space and time complexities in handling extensive scientific volumetric data, various data representations have been developed for the analysis of large-scale scientific data. Multivariate functional approximat
Externí odkaz:
http://arxiv.org/abs/2312.15073
Publikováno v:
In IEEE Transactions on Visualization & Computer Graphics, vol. 30, no. 01, pp. 965-974, 2024
Scene representation networks (SRNs) have been recently proposed for compression and visualization of scientific data. However, state-of-the-art SRNs do not adapt the allocation of available network parameters to the complex features found in scienti
Externí odkaz:
http://arxiv.org/abs/2308.02494
We present a neural network approach to compute stream functions, which are scalar functions with gradients orthogonal to a given vector field. As a result, isosurfaces of the stream function extract stream surfaces, which can be visualized to analyz
Externí odkaz:
http://arxiv.org/abs/2307.08142
B-spline models are a powerful way to represent scientific data sets with a functional approximation. However, these models can suffer from spurious oscillations when the data to be approximated are not uniformly distributed. Model regularization (i.
Externí odkaz:
http://arxiv.org/abs/2301.01209
3D volume rendering is widely used to reveal insightful intrinsic patterns of volumetric datasets across many domains. However, the complex structures and varying scales of volumetric data can make efficiently generating high-quality volume rendering
Externí odkaz:
http://arxiv.org/abs/2204.11762
B-spline models are a powerful way to represent scientific data sets with a functional approximation. However, these models can suffer from spurious oscillations when the data to be approximated are not uniformly distributed. Model regularization (i.
Externí odkaz:
http://arxiv.org/abs/2203.12730