PN 6-3

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

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1 to 10 of 55 Results

CatBoost-HPO_steps.tar.gz Nov 5, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data [NeurIPS, arXiv v2] Plain Text - 141.2 GB - MD5: a2cd5043064bd20b28f90dc724f7a4fd DATA
cv_refit.tar.gz Nov 5, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data [NeurIPS, arXiv v2] Plain Text - 90.5 GB - MD5: ea203d35daf3fe13e8c32b93d0488c0c DATA Results for inner cross-validation / refitting of RealMLP-TD and LGBM-TD.
FTT-HPO_steps.tar.gz Nov 5, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data [NeurIPS, arXiv v2] Plain Text - 16.7 GB - MD5: 6caba3a60faaad1b7a91b03e06c035d2 DATA
grinsztajn_benchmarking_code.zip Nov 5, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data [NeurIPS, arXiv v2] ZIP Archive - 1.1 MB - MD5: e4e6f5dca291e6c59f5135ab1a1d63a8 Code for running the old version of the Grinsztajn. et al (2022) benchmark with our models.
grinsztajn_results.csv.gz Nov 5, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data [NeurIPS, arXiv v2] Gzip Archive - 87.2 MB - MD5: 04efd949409a882d3fb3c18371d451fa Results on the old version of the Grinsztajn et al. (2022) benchmark.
LGBM-HPO_steps.tar.gz Nov 5, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data [NeurIPS, arXiv v2] Plain Text - 118.8 GB - MD5: d02951865e99ef832a137804cce02b47 DATA
main_no_results.tar.gz Nov 5, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data [NeurIPS, arXiv v2] Plain Text - 742.0 MB - MD5: 5f1adb9e84661fc6e40072000d8102e9 DATA Benchmark results data for all benchmarks. Contains result summaries (enough for plotting) but not the detailed results. After unpacking, rename the tasks_only_infos folder to tasks if you don't already have a tasks folder.
MLP-PLR-HPO_steps.tar.gz Nov 5, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data [NeurIPS, arXiv v2] Plain Text - 132.9 GB - MD5: 1dd142f1d8be3c22a530ea669368d9f0 DATA
MLP-RTDL-HPO_steps.tar.gz Nov 5, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data [NeurIPS, arXiv v2] Plain Text - 139.5 GB - MD5: e7c890f24d82ee6365b39f9da9a1b253 DATA
pytabkit_code.zip Nov 5, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data [NeurIPS, arXiv v2] ZIP Archive - 719.6 KB - MD5: c4803f9ed6ed2be89668af29f9720404 Contains the code for running the benchmarks, as well as an implementation of the models evaluated on these benchmarks. Also contains instructions in README.md as well as the documentation.

CatBoost-HPO_steps.tar.gz

Nov 5, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data [NeurIPS, arXiv v2]

Plain Text - 141.2 GB -

DATA

cv_refit.tar.gz

Nov 5, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data [NeurIPS, arXiv v2]

Plain Text - 90.5 GB -

DATA

Results for inner cross-validation / refitting of RealMLP-TD and LGBM-TD.

FTT-HPO_steps.tar.gz

Nov 5, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data [NeurIPS, arXiv v2]

Plain Text - 16.7 GB -

DATA

grinsztajn_benchmarking_code.zip

Nov 5, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data [NeurIPS, arXiv v2]

ZIP Archive - 1.1 MB -

Code for running the old version of the Grinsztajn. et al (2022) benchmark with our models.

grinsztajn_results.csv.gz

Nov 5, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data [NeurIPS, arXiv v2]

Gzip Archive - 87.2 MB -

Results on the old version of the Grinsztajn et al. (2022) benchmark.

LGBM-HPO_steps.tar.gz

Nov 5, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data [NeurIPS, arXiv v2]

Plain Text - 118.8 GB -

DATA

main_no_results.tar.gz

Nov 5, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data [NeurIPS, arXiv v2]

Plain Text - 742.0 MB -

DATA

Benchmark results data for all benchmarks. Contains result summaries (enough for plotting) but not the detailed results. After unpacking, rename the tasks_only_infos folder to tasks if you don't already have a tasks folder.

MLP-PLR-HPO_steps.tar.gz

Nov 5, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data [NeurIPS, arXiv v2]

Plain Text - 132.9 GB -

DATA

MLP-RTDL-HPO_steps.tar.gz

Nov 5, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data [NeurIPS, arXiv v2]

Plain Text - 139.5 GB -

DATA

pytabkit_code.zip

Nov 5, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data [NeurIPS, arXiv v2]

ZIP Archive - 719.6 KB -

Contains the code for running the benchmarks, as well as an implementation of the models evaluated on these benchmarks. Also contains instructions in README.md as well as the documentation.

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