All Steps: Pretrained Models

Version 1.0
Pelzer, Julia; Kotchourko, Serge, 2026, "All Steps: Pretrained Models", https://doi.org/10.18419/DARUS-6436, DaRUS, V1
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Description

Pretrained models for "Stepwise Benchmarking: Data-Scarce Groundwater Heat Pumps' Modeling"

This dataset contains the pretrained baseline models, namely CNO, ConvNeXt U-Net, DPOT, LGCNN, scOT, TFNO, and U-Net. A model is trained under a fixed budget on all three training steps in the benchmark and included if training is technically possible under these constraints.

The U-Net and LGCNN models are stored in .pt files, the default file type for the PyTorch library, with a configuration file in .yaml format containing the hyperparameters. The configuration file can be used to automatically instantiate the correct model with our Github repository: https://github.com/JuliaPelzer/Heat-Plume-Prediction/tree/AllIn1/LGCNN/benchmarkingdata (commit: 83bf879).
More details can be found in the implementation.

The training code for the other models is available at https://github.com/kotserge/benchmarking-heat-pump (commit: 1eb5e7a).

Automatic evaluation of all models can be obtained with https://github.com/JuliaPelzer/Stepwise-Benchmarking-HPs.

SWE models are trained on the data from Takamoto, Makoto; Praditia, Timothy; Leiteritz, Raphael; MacKinlay, Dan; Alesiani, Francesco; Pflüger, Dirk; Niepert, Mathias, 2022, "PDEBench Datasets", https://doi.org/10.18419/DARUS-2986, DaRUS, V8.
Subject Computer and Information Science; Earth and Environmental Sciences
Keyword Benchmark, Scientific Machine Learning, Groundwater Flow, Heat Pump, Groundwater, Heat Transport
License/Data Use Agreement

CC BY 4.0

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examples_allMo_allD_norm2.pdf
comparison_for_paper/Adobe PDF - 167.5 KB
Published Sep 14, 2026
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model_comparison.ipynb
comparison_for_paper/Jupyter Notebook - 396.7 KB
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model_ranking_transpose.pdf
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step1_metrics.yaml
Step_1/CNO/application/yaml - 1.8 KB
Published Sep 14, 2026
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step1_model.pt
Step_1/CNO/application/vnd.snesdev-page-table - 514.9 MB
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step1_training.zip
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predictions_test.h5
Step_1/CNO/step1TEST_predictions/Hierarchical Data Format - 262.4 MB
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step1_prediction900.pt
Step_1/CNO/step1TEST_predictions/application/vnd.snesdev-page-table - 6.3 MB
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step1_metrics.yaml
Step_1/ConvNeXt/application/yaml - 1.8 KB
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step1_model.pt
Step_1/ConvNeXt/application/vnd.snesdev-page-table - 491.3 MB
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Curation Status History
StatusDateAssigner
2026-09-14 10:29:15Julia Pelzer
Waiting for Feedback from Author2026-09-08 12:13:03Dataverse Admin
In Review by FoKUS2026-09-07 07:16:16Dataverse Admin
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