Stuttgart Center for Simulation Science (SC SimTech)

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25,541 to 25,550 of 25,658 Results

reconstructed_20201127_01.rar Mar 30, 2021 - Sample 1 of human femoral heads: micro-XRCT data sets RAR Archive - 23.8 GB - MD5: 526700772056245bbcbde7ebc70ddbd9 Reconstructed micro-XRCT data set in 16 bit *.tif file format. 2940x2940x2141 voxels with the uniform voxel size of 5.0 µm. Upper part scan.
Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression Mar 23, 2021 - PN 6-3 Holzmüller, David, 2021, "Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression", https://doi.org/10.18419/DARUS-1771, DaRUS, V1 This dataset contains code used to generate the figures in the paper On the Universality of the Double Descent Peak in Ridgeless Regression, David Holzmüller, International Conference on Learning Representations 2021. The code is also provided on GitHub. Here, we additionally provide the data that is generated by the code and that is required to ge...
computation.py Mar 23, 2021 - Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression Python Source Code - 16.2 KB - MD5: 727ea9050972d03f12c6aa5b32b7e37c
data.tar.gz Mar 23, 2021 - Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression Gzip Archive - 5.6 GB - MD5: 220970917c2371206a808c02bbb9f359 Data Data generated by running the code
main.py Mar 23, 2021 - Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression Python Source Code - 2.7 KB - MD5: d298130fc29f0a84b33b58ad0d100a06
plotting.py Mar 23, 2021 - Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression Python Source Code - 15.3 KB - MD5: 9017e22f361d3ee27b7fa52a241a2834
README.md Mar 23, 2021 - Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression Markdown Text - 1.6 KB - MD5: d2572a82e8003c56d0307012ac4069d8
sampling.py Mar 23, 2021 - Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression Python Source Code - 11.1 KB - MD5: 1a719b0984045eca7ce97bc54b4b9e2b
utils.py Mar 23, 2021 - Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression Python Source Code - 2.6 KB - MD5: f921b3cd6389ea9f8e4707a3655a75f7
PN 6-3(Institute for Stochastics and Applications, Universität Stuttgart) Mar 16, 2021PN 6 SimTech Project PN6-3 "Understanding Physical Constraints in Machine Learning for Simulation"

reconstructed_20201127_01.rar

Mar 30, 2021 - Sample 1 of human femoral heads: micro-XRCT data sets

RAR Archive - 23.8 GB -

Reconstructed micro-XRCT data set in 16 bit *.tif file format. 2940x2940x2141 voxels with the uniform voxel size of 5.0 µm. Upper part scan.

Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression

Mar 23, 2021 - PN 6-3

Holzmüller, David, 2021, "Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression", https://doi.org/10.18419/DARUS-1771, DaRUS, V1

This dataset contains code used to generate the figures in the paper On the Universality of the Double Descent Peak in Ridgeless Regression, David Holzmüller, International Conference on Learning Representations 2021. The code is also provided on GitHub. Here, we additionally provide the data that is generated by the code and that is required to ge...

computation.py

Mar 23, 2021 - Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression

Python Source Code - 16.2 KB -

data.tar.gz

Mar 23, 2021 - Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression

Gzip Archive - 5.6 GB -

Data

Data generated by running the code

main.py

Mar 23, 2021 - Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression

Python Source Code - 2.7 KB -

plotting.py

Mar 23, 2021 - Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression

Python Source Code - 15.3 KB -

README.md

Mar 23, 2021 - Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression

Markdown Text - 1.6 KB -

sampling.py

Mar 23, 2021 - Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression

Python Source Code - 11.1 KB -

utils.py

Mar 23, 2021 - Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression

Python Source Code - 2.6 KB -

PN 6-3(Institute for Stochastics and Applications, Universität Stuttgart)

Mar 16, 2021PN 6

SimTech Project PN6-3 "Understanding Physical Constraints in Machine Learning for Simulation"

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