SimTech Project PN6-3 "Understanding Physical Constraints in Machine Learning for Simulation"
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Plain Text - 129.4 GB - MD5: 18626c6d8e091db924ce74542bb7df80
DATA
Aug 8, 2024
Holzmüller, David; Grinsztajn, Léo; Steinwart, Ingo, 2024, "Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data", https://doi.org/10.18419/darus-4255, DaRUS, V1
This dataset contains code and data for our paper "Better by default: Strong pre-tuned MLPs and boosted trees on tabular data". The main code is provided in pytabkit_code.zip and contains further documentation in README.md and the docs folder. The main code is also provided on Gi...
Nov 5, 2024
Holzmüller, David; Grinsztajn, Léo; Steinwart, Ingo, 2024, "Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data [NeurIPS, arXiv v2]", https://doi.org/10.18419/darus-4555, DaRUS, V1
This dataset contains code and data for our paper "Better by default: Strong pre-tuned MLPs and boosted trees on tabular data", specifically, the NeurIPS version which is also the second version on arXiv. The main code is provided in pytabkit_code.zip and contains further documen...
Jun 20, 2022
Holzmüller, David; Steinwart, Ingo, 2022, "Code for: Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent", https://doi.org/10.18419/darus-2978, DaRUS, V1
This data set contains code used to generate figures and tables in our paper "Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent". The code is also available on GitHub. Information on the code and installation instructions can be found in the file README.md.
Python Source Code - 16.2 KB - MD5: 727ea9050972d03f12c6aa5b32b7e37c
Python Source Code - 58 B - MD5: 2b8520afbcb24f93040273f4edfee4b7
Plain Text - 90.5 GB - MD5: ea203d35daf3fe13e8c32b93d0488c0c
DATA
Results for inner cross-validation / refitting of RealMLP-TD and LGBM-TD.
Gzip Archive - 5.6 GB - MD5: 220970917c2371206a808c02bbb9f359
Data
Data generated by running the code
Python Source Code - 19.2 KB - MD5: 06303383461187b4df57f1e6a54afb12
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