Stuttgart Center for Simulation Science (SC SimTech)

EXC 2075 Project Networks

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19,111 to 19,120 of 25,353 Results

naive_approach_unetnopad.zip Sep 10, 2024 - Models and Prepared Datasets for LG-CNN ZIP Archive - 1.1 GB - MD5: c29a12ec324a3acc058049cdd599bc6d
predict_T 1dp.zip Sep 10, 2024 - Models and Prepared Datasets for LG-CNN ZIP Archive - 2.7 GB - MD5: 3eed4f7c5d51dc7c3f8b300e5b0379cd
predict_T based_on_predict_v.zip Sep 10, 2024 - Models and Prepared Datasets for LG-CNN ZIP Archive - 118.1 MB - MD5: e01e75ab31aef9eeedc425a07d336e59
predict_T unet.zip Sep 10, 2024 - Models and Prepared Datasets for LG-CNN ZIP Archive - 178.2 MB - MD5: 073be216ae8d524c369ef77e511105e4
preCICE-v3.1.2.tar.gz Aug 23, 2024 - Replication Data for: Partitioned Multiphysics Simulation of an Electrophysiological Three-Tendon-Biceps Model Gzip Archive - 1.6 MB - MD5: 3b9e8d6e243f77215e997d0f68fe17c5 The preCICE version used for the experiments
CatBoost-HPO_steps.tar.gz Aug 8, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data Plain Text - 129.4 GB - MD5: 18626c6d8e091db924ce74542bb7df80 DATA
grinsztajn_benchmarking_code.zip Aug 8, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data ZIP Archive - 1.1 MB - MD5: e4e6f5dca291e6c59f5135ab1a1d63a8 Code for running the Grinsztajn. et al (2022) benchmark with our models.
grinsztajn_results.csv.gz Aug 8, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data Gzip Archive - 87.2 MB - MD5: 04efd949409a882d3fb3c18371d451fa Results on the Grinsztajn et al. (2022) benchmark.
LGBM-HPO_steps.tar.gz Aug 8, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data Plain Text - 107.9 GB - MD5: 63faf9208e0831c1eeda073b73302ccf DATA
main_no_results.tar.gz Aug 8, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data Plain Text - 555.1 MB - MD5: 9e1b8e3d2f905725b90fd498435245e4 DATA Benchmark results data for meta-train and meta-test benchmarks. Contains result summaries (enough for plotting) but not the detailed results.

naive_approach_unetnopad.zip

Sep 10, 2024 - Models and Prepared Datasets for LG-CNN

ZIP Archive - 1.1 GB -

predict_T 1dp.zip

Sep 10, 2024 - Models and Prepared Datasets for LG-CNN

ZIP Archive - 2.7 GB -

predict_T based_on_predict_v.zip

Sep 10, 2024 - Models and Prepared Datasets for LG-CNN

ZIP Archive - 118.1 MB -

predict_T unet.zip

Sep 10, 2024 - Models and Prepared Datasets for LG-CNN

ZIP Archive - 178.2 MB -

preCICE-v3.1.2.tar.gz

Aug 23, 2024 - Replication Data for: Partitioned Multiphysics Simulation of an Electrophysiological Three-Tendon-Biceps Model

Gzip Archive - 1.6 MB -

The preCICE version used for the experiments

CatBoost-HPO_steps.tar.gz

Aug 8, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data

Plain Text - 129.4 GB -

DATA

grinsztajn_benchmarking_code.zip

Aug 8, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data

ZIP Archive - 1.1 MB -

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

grinsztajn_results.csv.gz

Aug 8, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data

Gzip Archive - 87.2 MB -

Results on the Grinsztajn et al. (2022) benchmark.

LGBM-HPO_steps.tar.gz

Aug 8, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data

Plain Text - 107.9 GB -

DATA

main_no_results.tar.gz

Aug 8, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data

Plain Text - 555.1 MB -

DATA

Benchmark results data for meta-train and meta-test benchmarks. Contains result summaries (enough for plotting) but not the detailed results.

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