Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v1]

DOI

This dataset contains code and data for 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.

Basic instructions for installing and running the software can be found in the README.md file.

Identifier
DOI https://doi.org/10.18419/darus-2615
Metadata Access https://darus.uni-stuttgart.de/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.18419/darus-2615
Provenance
Creator Holzmüller, David ORCID logo; Zaverkin, Viktor ORCID logo; Kästner, Johannes ORCID logo; Steinwart, Ingo ORCID logo
Publisher DaRUS
Contributor Holzmüller, David; Steinwart, Ingo
Publication Year 2022
Funding Reference DFG EXC 2075 - 390740016 ; German Academic Scholarship Foundation
Rights info:eu-repo/semantics/restrictedAccess
OpenAccess false
Contact Holzmüller, David (Universität Stuttgart); Steinwart, Ingo (Universität Stuttgart)
Representation
Resource Type Dataset
Format text/x-python; application/x-ipynb+json; application/octet-stream; application/gzip; text/plain; charset=US-ASCII; text/markdown; text/plain
Size 26715; 22655; 114203; 3368; 498; 15726; 1060433810; 26905; 23120; 41911; 19168; 27237; 0; 8753; 4011; 11357; 645; 394; 52095868; 28318; 5212; 2174; 606; 94461229; 6503; 26535; 23699; 15167; 1555; 11057; 180183; 7540; 3010
Version 1.0
Discipline Other