Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression arXiv v3
D. Holzmüller, V. Zaverkin, J. Kästner, and I. Steinwart. Software, (2023)Related to: David Holzmüller, Viktor Zaverkin, Johannes Kästner, and Ingo Steinwart. A Framework and Benchmark for Deep Batch Active Learning for Regression, 2023. arXiv: 2203.09410.
DOI: 10.18419/darus-3394
Abstract
This dataset contains code and data for the third arXiv version of our paper Ä Framework and Benchmark for Deep Batch Active Learning for Regression". The code can be used to reproduce the results, to benchmark new methods, or to apply the presented methods to new Deep Batch Active Learning problems. The code is also available on GitHub. Information on the code can be found in the file README.md and in the Jupyter notebooks in the examples folder. Additionally, we provide the files results.tar.gz and plots.tar.gz which contain generated data and plots. These files can be unpacked in folders specified in custom_paths.py (see README.md) and can be used as described in examples/benchmark.ipynb.
Related to: David Holzmüller, Viktor Zaverkin, Johannes Kästner, and Ingo Steinwart. A Framework and Benchmark for Deep Batch Active Learning for Regression, 2023. arXiv: 2203.09410
%0 Generic
%1 holzmuller2023framework
%A Holzmüller, David
%A Zaverkin, Viktor
%A Kästner, Johannes
%A Steinwart, Ingo
%D 2023
%K darus mult ubs_10003 ubs_10008 ubs_10021 ubs_20003 ubs_20013 ubs_20019 ubs_30039 ubs_30126 ubs_30165 ubs_40065 ubs_40202 unibibliografie
%R 10.18419/darus-3394
%T Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression arXiv v3
%X This dataset contains code and data for the third arXiv version of our paper Ä Framework and Benchmark for Deep Batch Active Learning for Regression". The code can be used to reproduce the results, to benchmark new methods, or to apply the presented methods to new Deep Batch Active Learning problems. The code is also available on GitHub. Information on the code can be found in the file README.md and in the Jupyter notebooks in the examples folder. Additionally, we provide the files results.tar.gz and plots.tar.gz which contain generated data and plots. These files can be unpacked in folders specified in custom_paths.py (see README.md) and can be used as described in examples/benchmark.ipynb.
@misc{holzmuller2023framework,
abstract = {This dataset contains code and data for the third arXiv version of our paper "A Framework and Benchmark for Deep Batch Active Learning for Regression". The code can be used to reproduce the results, to benchmark new methods, or to apply the presented methods to new Deep Batch Active Learning problems. The code is also available on GitHub. Information on the code can be found in the file README.md and in the Jupyter notebooks in the examples folder. Additionally, we provide the files results.tar.gz and plots.tar.gz which contain generated data and plots. These files can be unpacked in folders specified in custom_paths.py (see README.md) and can be used as described in examples/benchmark.ipynb. },
added-at = {2023-04-11T07:20:44.000+0200},
affiliation = {Holzmüller, David/Universität Stuttgart, Zaverkin, Viktor/Universität Stuttgart, Kästner, Johannes/Universität Stuttgart, Steinwart, Ingo/Universität Stuttgart},
author = {Holzmüller, David and Zaverkin, Viktor and Kästner, Johannes and Steinwart, Ingo},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/22f7b69568c13e2d6c9f8cb40eac4a327/unibiblio},
doi = {10.18419/darus-3394},
howpublished = {Software},
interhash = {cfae73101d08591f96f7eaac4fe3e7ac},
intrahash = {2f7b69568c13e2d6c9f8cb40eac4a327},
keywords = {darus mult ubs_10003 ubs_10008 ubs_10021 ubs_20003 ubs_20013 ubs_20019 ubs_30039 ubs_30126 ubs_30165 ubs_40065 ubs_40202 unibibliografie},
note = {Related to: David Holzmüller, Viktor Zaverkin, Johannes Kästner, and Ingo Steinwart. A Framework and Benchmark for Deep Batch Active Learning for Regression, 2023. arXiv: 2203.09410},
orcid-numbers = {Holzmüller, David/0000-0002-9443-0049, Zaverkin, Viktor/0000-0001-9940-8548, Kästner, Johannes/0000-0001-6178-7669, Steinwart, Ingo/0000-0002-4436-7109},
timestamp = {2023-04-11T07:20:44.000+0200},
title = {Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v3]},
year = 2023
}