25,281 to 25,290 of 25,382 Results
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 generated by running the code |
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
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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
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Mar 23, 2021 -
Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression
Markdown Text - 1.6 KB -
MD5: d2572a82e8003c56d0307012ac4069d8
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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
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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
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Mar 16, 2021PN 6
SimTech Project PN6-3 "Understanding Physical Constraints in Machine Learning for Simulation" |
Mar 12, 2021Stochastic Simulation and Safety Research for Hydrosystems (LS3)
This dataverse contains modeling data (percolation type) and comparison methods (codes) for the project models for gas migration in porous media. |
Mar 12, 2021Projects without PN Affiliation
This dataverse contains data associated with the projects (as sub-dataverses) of LS3. |
Mar 11, 2021 -
micro-XRCT dataset of Enzymatically Induced Calcite Precipitation (EICP) in a microfluidic cell
TAR Archive - 2.6 MB -
MD5: d1931812fadb61cb603eab992e8542db
This dataset is the transformed, cutted and processed version of the XRCT images. It contains the 20 binarized slices with the precipitates flagged as 1.
The size of the volume is 89 mm x 22 mm x 0.085 mm. |
