1 to 10 of 102 Results
Keim, Leon; Class, Holger, 2024, "Replication Data for: Rayleigh invariance allows the estimation of effective CO2 fluxes due to convective dissolution into water-filled fractures", https://doi.org/10.18419/darus-4143, DaRUS, V1
This dataset features both data and code related to the research article titled "Rayleigh Invariance Enables Estimation of Effective CO2 Fluxes Resulting from Convective Dissolution in Water-Filled Fractures." It includes raw data packaged in tarball format, including Python scri... |
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Keim, Leon; Class, Holger, 2024, "Replication Code for: Rayleigh invariance allows the estimation of effective CO2 fluxes due to convective dissolution into water-filled fractures", https://doi.org/10.18419/darus-4089, DaRUS, V1
This dataset consists of software code associated with the publication titled "Rayleigh Invariance Enables Estimation of Effective CO2 Fluxes Resulting from Convective Dissolution in Water-Filled Fractures." It includes a Dockerimage that contains the precompiled code for immedia... |
Apr 9, 2024 - Surrogate models for groundwater flow simulations
Pelzer, Julia, 2024, "Raw Simulation Datasets for Extending Heat Plumes", https://doi.org/10.18419/darus-4133, DaRUS, V1
These data sets serve as training and testing data for modelling the extension of temperature field emanating from one groundwater heat pump. There are simulated with Pflotran and saved in h5 format. The data set for training is called "dataset_medium_k_3e-10_1000dp". It contains... |
Apr 2, 2024 - Surrogate models for groundwater flow simulations
Pelzer, Julia, 2024, "Models and Prepared Datasets for the Second Stage", https://doi.org/10.18419/darus-3689, DaRUS, V1
Models trained with Heat Plume Prediction and datasets prepared with Heat Plume Prediction into reasonable format + normalization etc, used for training these models. Last relevant git commit: 5d6c5eae5b00e438. Based on raw data from doi:darus-3651 and doi:darus-3652. |
Apr 2, 2024 - Surrogate models for groundwater flow simulations
Pelzer, Julia, 2024, "Models and Prepared Datasets for the First Stage", https://doi.org/10.18419/darus-3690, DaRUS, V1
Models trained with Heat Plume Prediction and datasets prepared with Heat Plume Prediction into reasonable format + normalization etc, used for training these models. Last relevant git commit: 5d6c5eae5b00e438. Based on raw data from doi:10.18419/darus-3649 and doi:10.18419/darus... |
Mar 27, 2024 - Publication Tools
Roy, Sarbani; Wang, Fangfang; Gläser, Dennis, 2024, "Harvester-Curator, a tool to elevate metadata provision in data and/or software repositories", https://doi.org/10.18419/darus-3785, DaRUS, V1
Harvester-Curator is a tool, designed to elevate metadata provision in data repositories. In the first phase, Harvester-Curator acts as a scanner, navigating through user code and/or data repositories to identify suitable parsers for different file types. It collects metadata fro... |
Reiser, Philipp; Aguilar, Javier Enrique; Guthke, Anneli; Bürkner, Paul-Christian, 2024, "Replication Code for: Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference", https://doi.org/10.18419/darus-4093, DaRUS, V1
This code allows to replicate key experiments from our paper: Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference. For further details, please refer to the README.md. |
Mar 14, 2024 - PN 6A-4
Alvarez Chaves, Manuel; Gupta, Hoshin; Ehret, Uwe; Guthke, Anneli, 2024, "Replication Data for: Evaluating Non-Parametric Methods in Information Theory", https://doi.org/10.18419/darus-4087, DaRUS, V1
Non-Parametric Estimation in Information Theory 1. Introduction This is a repository for our paper on: "Evaluating Density- and Nearest Neighbor-based Methods to Accurately Estimate Information-Theoretic Quantities from Multi-Dimensional Sample Data". The projects is organizes as... |
Mar 13, 2024PN 2
SimTech Project PN 2-7 "Data-integrated training of surrogate models for uncertainty quantification and diagnostics of complex biological systems models" |
