4 papers
REV-INR: Regularized Evidential Implicit Neural Representation for Uncertainty-Aware Volume Visualization
Shanu Saklani, Tushar M. Athawale, Nairita Pal +3
Applications of Implicit Neural Representations (INRs) have emerged as a promising deep learning approach for compactly representing large volumetric datasets. These models can act…
Efficient Probabilistic Visualization of Local Divergence of 2D Vector Fields with Independent Gaussian Uncertainty
Timbwaoga A. J. Ouermi, Eric Li, Kenneth Moreland +3
This work focuses on visualizing uncertainty of local divergence of two-dimensional vector fields. Divergence is one of the fundamental attributes of fluid flows, as it can help do…
Uncertainty-Informed Volume Visualization using Implicit Neural Representation
Shanu Saklani, Chitwan Goel, Shrey Bansal +5
The increasing adoption of Deep Neural Networks (DNNs) has led to their application in many challenging scientific visualization tasks. While advanced DNNs offer impressive general…
Uncertainty Visualization of Critical Points of 2D Scalar Fields for Parametric and Nonparametric Probabilistic Models
Tushar M. Athawale, Zhe Wang, David Pugmire +5
This paper presents a novel end-to-end framework for closed-form computation and visualization of critical point uncertainty in 2D uncertain scalar fields. Critical points are fund…