Uncertainty Visualization

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

5 shown of 5 papers with code (10 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• VOICE: Variance of Induced Contrastive Explanations to quantify Uncertainty in Neural Network Interpretability
  1 Jun 2024 1 repository listed
  We show that every image, network, prediction, and explanatory technique has a unique uncertainty.
• Uncertainty Visualization via Low-Dimensional Posterior Projections
  12 Dec 2023 1 repository listed
  In ill-posed inverse problems, it is commonly desirable to obtain insight into the full spectrum of plausible solutions, rather than extracting only a single reconstruction.
• On the Posterior Distribution in Denoising: Application to Uncertainty Quantification
  24 Sep 2023 1 repository listed Syntology ran 6 of 8 samples · 2 unverified
  Denoisers play a central role in many applications, from noise suppression in low-grade imaging sensors, to empowering score-based generative models.
• Affective Medical Estimation and Decision Making via Visualized Learning and Deep Learning
  9 May 2022 1 repository listed
  With the advent of sophisticated machine learning (ML) techniques and the promising results they yield, especially in medical applications, where they have been investigated for different tasks to enhance the…
• Joint Segmentation and Uncertainty Visualization of Retinal Layers in Optical Coherence Tomography Images using Bayesian Deep Learning
  12 Sep 2018 1 repository listed
  Optical coherence tomography (OCT) is commonly used to analyze retinal layers for assessment of ocular diseases.

Syntology lines on 1 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.