DaRUS

Metrics

3,798,507 Downloads

Featured Dataverses

In order to use this feature you must have at least one published or linked dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

License: Custom Terms

15,681 to 15,690 of 16,109 Results

tutorials-202202.0.tar.gz Apr 21, 2022 - preCICE Distribution Version v2202.0 Gzip Archive - 6.2 MB - MD5: 5ecd80d21a52ee688ea50a635c1d4f7b Tutorial cases for preCICE with real solvers
vm-202202.0.0.tar.gz Apr 21, 2022 - preCICE Distribution Version v2202.0 Gzip Archive - 10.3 KB - MD5: 644cac05029e4c4b7c2f15b97e97454b Vagrant box with preCICE and examples preinstalled
algorithms.py Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1] Python Source Code - 26.1 KB - MD5: 135174e733df1a4b2987aa0cb450c4a3
analysis.py Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1] Python Source Code - 22.1 KB - MD5: 50ac2de7ed2628a62f3ea8727751e027
benchmark.ipynb Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1] Jupyter Notebook - 111.5 KB - MD5: 96b0ac084968162443906c31b9a16dbf
check_task_learnability.py Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1] Python Source Code - 3.3 KB - MD5: 3589368ab168cf46c8a7222f1e2acf29
custom_paths.py.default Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1] Unknown - 498 B - MD5: 0aa70e1f521326332f33f70b938dc292
data.py Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1] Python Source Code - 15.4 KB - MD5: 5c2cdd3bdee3b38e4fddb8b7a2d7fec8
data.tar.gz Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1] Gzip Archive - 1011.3 MB - MD5: 2b34cf7ecdb8fa51046ade430586c22e Compressed folder containing downloaded raw and processed data sets as generated by download_data.py at the time of running the experiments.
download_data.py Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1] Python Source Code - 26.3 KB - MD5: 0994f8b09885fc142fc3c54edea4af23

tutorials-202202.0.tar.gz

Apr 21, 2022 - preCICE Distribution Version v2202.0

Gzip Archive - 6.2 MB -

Tutorial cases for preCICE with real solvers

vm-202202.0.0.tar.gz

Apr 21, 2022 - preCICE Distribution Version v2202.0

Gzip Archive - 10.3 KB -

Vagrant box with preCICE and examples preinstalled

algorithms.py

Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1]

Python Source Code - 26.1 KB -

analysis.py

Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1]

Python Source Code - 22.1 KB -

benchmark.ipynb

Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1]

Jupyter Notebook - 111.5 KB -

check_task_learnability.py

Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1]

Python Source Code - 3.3 KB -

custom_paths.py.default

Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1]

Unknown - 498 B -

data.py

Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1]

Python Source Code - 15.4 KB -

data.tar.gz

Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1]

Gzip Archive - 1011.3 MB -

Compressed folder containing downloaded raw and processed data sets as generated by download_data.py at the time of running the experiments.

download_data.py

Apr 13, 2022 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1]

Python Source Code - 26.3 KB -

Add Data

Share Dataverse

Link Dataverse

Reset Modifications