SFB-TRR 161 A01 "Uncertainty Quantification and Analysis in Visual Computing"

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111 to 120 of 2,159 Results

supplementary.pdf Sep 16, 2024 - Supplementary Material for Uncertainty-aware Spectral Visualization Adobe PDF - 1.2 MB - MD5: fe2fd8c5657618b68619ddcf155e10b9 The supplemental material which contains mathematical derivations for the results presented in the main paper, a comparison to Monte Carlo sampling and additional use cases.
video.mp4 Sep 16, 2024 - Supplementary Material for Uncertainty-aware Spectral Visualization MPEG-4 Video - 11.4 MB - MD5: 056e8ced50d7010a4b3a53c8db8dcaed A video that shows how the visual analysis approach can be used for uncertainty-aware spectral analaysis.
Supplemental Material for Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions Sep 2, 2024 Reichmann, Luca; Hägele, David; Weiskopf, Daniel, 2024, "Supplemental Material for Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions", https://doi.org/10.18419/DARUS-4441, DaRUS, V1, UNF:6:WoQ4MNffz92VcvZ/qCGL5w== [fileUNF] This dataset contains the supplemental material for "Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions". The contents and usage of this dataset are described in the README.md files.
amiramesh.py Sep 2, 2024 - Supplemental Material for Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions Python Source Code - 1.6 KB - MD5: f46840a8ba5f5eb6c0cd448328d45eb6 Code
download_embeddings.py Sep 2, 2024 - Supplemental Material for Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions Python Source Code - 1.7 KB - MD5: 9e512511bd521fe8dc7f5e48adaec823 script to download all of the embeddings. On command line use: python3 download_embeddings.py
download_images.py Sep 2, 2024 - Supplemental Material for Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions Python Source Code - 1.5 KB - MD5: ed4de7d69bd1fade0bbfe5d9f17fe968 script to download all images. On command line use: python3 download_images.py
download.sh Sep 2, 2024 - Supplemental Material for Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions Shell Script - 821 B - MD5: a43a6368829cde23690be83cb7b85f8a Code
flows.py Sep 2, 2024 - Supplemental Material for Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions Python Source Code - 9.4 KB - MD5: 010dc37db9478df3ccfc301d1cda4410 Code
mds_demo.py Sep 2, 2024 - Supplemental Material for Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions Python Source Code - 5.4 KB - MD5: 9597d85c23b98e62ba3b002d68027263 Code
metric_script.py Sep 2, 2024 - Supplemental Material for Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions Python Source Code - 5.6 KB - MD5: 8b51026b05787274bd81faf6ee592031 Code

supplementary.pdf

Sep 16, 2024 - Supplementary Material for Uncertainty-aware Spectral Visualization

Adobe PDF - 1.2 MB -

The supplemental material which contains mathematical derivations for the results presented in the main paper, a comparison to Monte Carlo sampling and additional use cases.

video.mp4

Sep 16, 2024 - Supplementary Material for Uncertainty-aware Spectral Visualization

MPEG-4 Video - 11.4 MB -

A video that shows how the visual analysis approach can be used for uncertainty-aware spectral analaysis.

Supplemental Material for Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions

Sep 2, 2024

Reichmann, Luca; Hägele, David; Weiskopf, Daniel, 2024, "Supplemental Material for Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions", https://doi.org/10.18419/DARUS-4441, DaRUS, V1, UNF:6:WoQ4MNffz92VcvZ/qCGL5w== [fileUNF]

This dataset contains the supplemental material for "Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions". The contents and usage of this dataset are described in the README.md files.

amiramesh.py

Sep 2, 2024 - Supplemental Material for Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions

Python Source Code - 1.6 KB -

Code

download_embeddings.py

Sep 2, 2024 - Supplemental Material for Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions

Python Source Code - 1.7 KB -

script to download all of the embeddings. On command line use: python3 download_embeddings.py

download_images.py

Sep 2, 2024 - Supplemental Material for Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions

Python Source Code - 1.5 KB -

script to download all images. On command line use: python3 download_images.py