Stuttgart Center for Simulation Science (SC SimTech)

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1 to 10 of 363 Results

Replication Data for: Interpreting learning dynamics of autoencoders: Transient scaling and emerging concepts of the Ising model Jul 22, 2026 - Studying Dynamical Systems for Intelligible Modeling and Unconventional Computing Weinmann, Max; Klopotek, Miriam, 2026, "Replication Data for: Interpreting learning dynamics of autoencoders: Transient scaling and emerging concepts of the Ising model", https://doi.org/10.18419/DARUS-6128, DaRUS, V1 This dataset contains all relevant data to reproduce the results of the paper titled "Interpreting learning dynamics of autoencoders: Transient scaling and emerging concepts of the Ising model" and supplementary figures. "code.tar.xz" contains the code to generate the datasets and model checkpoints used in the analysis. Information on the code incl...
Replication Data for: Symplecticity-Preserving Prediction of Hamiltonian Dynamics by Generalized Kernel Interpolation Jul 17, 2026 - Projects without PN Affiliation Herkert, Robin, 2026, "Replication Data for: Symplecticity-Preserving Prediction of Hamiltonian Dynamics by Generalized Kernel Interpolation", https://doi.org/10.18419/DARUS-5644, DaRUS, V1 This dataset includes the code and numerical data to reproduce the results from the paper titled "Symplecticity-Preserving Prediction of Hamiltonian Dynamics by Generalized Kernel Interpolation" (2026). It contains the nonparametric variant, in which the surrogate model is trained for one fixed Hamiltonian system and one prescribed macro time step...
Replication Data for: AI-Assisted RDF Authoring from JSON Data Jul 10, 2026 - Usability and Sustainability of Simulation Software Neubauer, Felix, 2026, "Replication Data for: AI-Assisted RDF Authoring from JSON Data", https://doi.org/10.18419/DARUS-6299, DaRUS, V1, UNF:6:j3H34z5Ux4jb6/he8Hprww== [fileUNF] This dataset accompanies the paper AI-Assisted RDF Authoring from JSON Data. It contains the metal-organic framework (MOF) synthesis JSON input used in the paper, the natural-language hints submitted to MetaConfigurator's AI assistant, the RML mappings generated from those hints, the RDF (JSON-LD) results obtained by executing the mappings, the SHA...
The DUNE-Phasefield Module (release 2.0) Jun 25, 2026 - PN 5-13 Riethmüller, Cedric, 2026, "The DUNE-Phasefield Module (release 2.0)", https://doi.org/10.18419/DARUS-6262, DaRUS, V1 The dune-phasefield module contains local operators and grid function spaces for the solution of Cahn-Hilliard and coupled Cahn-Hilliard Navier-Stokes systems in a FEM framework. The module additionally provides option-classes for physical properties, multiple Cahn-Hilliard potentials, a time-step manager and grid adaptivity. Compared to the initia...
Replication Data for: A variational approach at uncertainty estimation in data-driven rainfall-runoff modeling Jun 22, 2026 - PN 6A-4 Álvarez Chaves, Manuel, 2026, "Replication Data for: A variational approach at uncertainty estimation in data-driven rainfall-runoff modeling", https://doi.org/10.18419/DARUS-5118, DaRUS, V1 This is repository contains code and archived results for the paper "A variational approach at uncertainty estimation in rainfall-runoff modeling" submitted for review to the ML:Earth journal. Instructions for running the training or evaluation workflows can be found in the README.md file located within the scripts/ folder. This dataset primarily c...
Replication Data for: Optimal information injection and transfer mechanisms for active matter reservoir computing (Gaimann and Klopotek, 2025) Jun 19, 2026 - PN 6-15 Gaimann, Mario U.; Klopotek, Miriam, 2025, "Replication Data for: Optimal information injection and transfer mechanisms for active matter reservoir computing (Gaimann and Klopotek, 2025)", https://doi.org/10.18419/DARUS-4805, DaRUS, V3, UNF:6:C1gH8zVD6YKFF/O3ZhSaSA== [fileUNF] This repository contains raw and post-processed replication data for the publication "Optimal information injection and transfer mechanisms for active matter reservoir computing" (Gaimann and Klopotek, 2025). The datasets contain physical observables recorded during non-equilibrium simulations of active matter systems (swarms) driven by an external...
Supplementary Videos for: Optimal information injection and transfer mechanisms for active matter reservoir computing (Gaimann and Klopotek, 2025) Jun 19, 2026 - PN 6-15 Gaimann, Mario U.; Klopotek, Miriam, 2025, "Supplementary Videos for: Optimal information injection and transfer mechanisms for active matter reservoir computing (Gaimann and Klopotek, 2025)", https://doi.org/10.18419/DARUS-4806, DaRUS, V3 This dataset contains supplementary videos for the publication "Optimal information injection and transfer mechanisms for active matter reservoir computing" (Gaimann and Klopotek, 2025) (to be published). The datasets contain physical observables recorded during non-equilibrium simulations of active matter systems (swarms) driven by an external for...
Replication Data for: Symplecticity-preserving prediction of parameter-dependent Hamiltonian dynamics by generalized kernel interpolation Jun 18, 2026 - Projects without PN Affiliation Herkert, Robin, 2026, "Replication Data for: Symplecticity-preserving prediction of parameter-dependent Hamiltonian dynamics by generalized kernel interpolation", https://doi.org/10.18419/DARUS-6155, DaRUS, V1 This dataset includes the code and numerical data to reproduce the results from the paper titled "Symplecticity-preserving prediction of parameter-dependent Hamiltonian dynamics by generalized kernel interpolation" (2026). The data were generated by the provided Python scripts from Hamiltonian test systems and are organized according to the corresp...
Replication data for: Orchestrating Schema Conversions Across Heterogeneous Schema Languages: A Graph-Based, Black-Box Approach Jun 18, 2026 - Usability and Sustainability of Simulation Software Neubauer, Felix, 2026, "Replication data for: Orchestrating Schema Conversions Across Heterogeneous Schema Languages: A Graph-Based, Black-Box Approach", https://doi.org/10.18419/DARUS-6158, DaRUS, V2, UNF:6:MTCchV/htouIGFqJY7cJug== [fileUNF] This dataset accompanies the paper "Orchestrating Schema Conversions Across Heterogeneous Schema Languages: A Graph-Based, Black-Box Approach" and contains source code snapshots, evaluation inputs, and evaluation outputs for the Schema Conversion Orchestrator and its integration into the MetaConfigurator tool. The dataset includes a snapshot of the...
Data for "Anion Effects in Electrochemical Transistors with Semiconducting Single-Walled Carbon Nanotube Networks" Jun 17, 2026 - Zaumseil group Dataverse Xu, Xuqiang; Fresta, Elisa; Lindenthal, Sebastian; Michel, Edwin; Zaumseil, Jana, 2026, "Data for "Anion Effects in Electrochemical Transistors with Semiconducting Single-Walled Carbon Nanotube Networks"", https://doi.org/10.18419/DARUS-5338, DaRUS, V1 This dataset contains all data underlying the figures in the paper "Anion Effects in Electrochemical Transistors with Semiconducting Single-Walled Carbon Nanotube Networks" (including the supporting information). Abbreviations used in the headers of the txt-files: Id: drain current Ig: gate (leakage) current gm: transconductance L: channel length W...

Replication Data for: Interpreting learning dynamics of autoencoders: Transient scaling and emerging concepts of the Ising model

Jul 22, 2026 - Studying Dynamical Systems for Intelligible Modeling and Unconventional Computing

Weinmann, Max; Klopotek, Miriam, 2026, "Replication Data for: Interpreting learning dynamics of autoencoders: Transient scaling and emerging concepts of the Ising model", https://doi.org/10.18419/DARUS-6128, DaRUS, V1

This dataset contains all relevant data to reproduce the results of the paper titled "Interpreting learning dynamics of autoencoders: Transient scaling and emerging concepts of the Ising model" and supplementary figures. "code.tar.xz" contains the code to generate the datasets and model checkpoints used in the analysis. Information on the code incl...

Replication Data for: Symplecticity-Preserving Prediction of Hamiltonian Dynamics by Generalized Kernel Interpolation

Jul 17, 2026 - Projects without PN Affiliation

Herkert, Robin, 2026, "Replication Data for: Symplecticity-Preserving Prediction of Hamiltonian Dynamics by Generalized Kernel Interpolation", https://doi.org/10.18419/DARUS-5644, DaRUS, V1

This dataset includes the code and numerical data to reproduce the results from the paper titled "Symplecticity-Preserving Prediction of Hamiltonian Dynamics by Generalized Kernel Interpolation" (2026). It contains the nonparametric variant, in which the surrogate model is trained for one fixed Hamiltonian system and one prescribed macro time step...

Replication Data for: AI-Assisted RDF Authoring from JSON Data

Jul 10, 2026 - Usability and Sustainability of Simulation Software

Neubauer, Felix, 2026, "Replication Data for: AI-Assisted RDF Authoring from JSON Data", https://doi.org/10.18419/DARUS-6299, DaRUS, V1, UNF:6:j3H34z5Ux4jb6/he8Hprww== [fileUNF]

This dataset accompanies the paper AI-Assisted RDF Authoring from JSON Data. It contains the metal-organic framework (MOF) synthesis JSON input used in the paper, the natural-language hints submitted to MetaConfigurator's AI assistant, the RML mappings generated from those hints, the RDF (JSON-LD) results obtained by executing the mappings, the SHA...

The DUNE-Phasefield Module (release 2.0)

Jun 25, 2026 - PN 5-13

Riethmüller, Cedric, 2026, "The DUNE-Phasefield Module (release 2.0)", https://doi.org/10.18419/DARUS-6262, DaRUS, V1

The dune-phasefield module contains local operators and grid function spaces for the solution of Cahn-Hilliard and coupled Cahn-Hilliard Navier-Stokes systems in a FEM framework. The module additionally provides option-classes for physical properties, multiple Cahn-Hilliard potentials, a time-step manager and grid adaptivity. Compared to the initia...

Replication Data for: A variational approach at uncertainty estimation in data-driven rainfall-runoff modeling

Jun 22, 2026 - PN 6A-4

Álvarez Chaves, Manuel, 2026, "Replication Data for: A variational approach at uncertainty estimation in data-driven rainfall-runoff modeling", https://doi.org/10.18419/DARUS-5118, DaRUS, V1

This is repository contains code and archived results for the paper "A variational approach at uncertainty estimation in rainfall-runoff modeling" submitted for review to the ML:Earth journal. Instructions for running the training or evaluation workflows can be found in the README.md file located within the scripts/ folder. This dataset primarily c...

Replication Data for: Optimal information injection and transfer mechanisms for active matter reservoir computing (Gaimann and Klopotek, 2025)

Jun 19, 2026 - PN 6-15

Gaimann, Mario U.; Klopotek, Miriam, 2025, "Replication Data for: Optimal information injection and transfer mechanisms for active matter reservoir computing (Gaimann and Klopotek, 2025)", https://doi.org/10.18419/DARUS-4805, DaRUS, V3, UNF:6:C1gH8zVD6YKFF/O3ZhSaSA== [fileUNF]

This repository contains raw and post-processed replication data for the publication "Optimal information injection and transfer mechanisms for active matter reservoir computing" (Gaimann and Klopotek, 2025). The datasets contain physical observables recorded during non-equilibrium simulations of active matter systems (swarms) driven by an external...

Supplementary Videos for: Optimal information injection and transfer mechanisms for active matter reservoir computing (Gaimann and Klopotek, 2025)

Jun 19, 2026 - PN 6-15

Gaimann, Mario U.; Klopotek, Miriam, 2025, "Supplementary Videos for: Optimal information injection and transfer mechanisms for active matter reservoir computing (Gaimann and Klopotek, 2025)", https://doi.org/10.18419/DARUS-4806, DaRUS, V3

This dataset contains supplementary videos for the publication "Optimal information injection and transfer mechanisms for active matter reservoir computing" (Gaimann and Klopotek, 2025) (to be published). The datasets contain physical observables recorded during non-equilibrium simulations of active matter systems (swarms) driven by an external for...

Replication Data for: Symplecticity-preserving prediction of parameter-dependent Hamiltonian dynamics by generalized kernel interpolation

Jun 18, 2026 - Projects without PN Affiliation

Herkert, Robin, 2026, "Replication Data for: Symplecticity-preserving prediction of parameter-dependent Hamiltonian dynamics by generalized kernel interpolation", https://doi.org/10.18419/DARUS-6155, DaRUS, V1

This dataset includes the code and numerical data to reproduce the results from the paper titled "Symplecticity-preserving prediction of parameter-dependent Hamiltonian dynamics by generalized kernel interpolation" (2026). The data were generated by the provided Python scripts from Hamiltonian test systems and are organized according to the corresp...

Replication data for: Orchestrating Schema Conversions Across Heterogeneous Schema Languages: A Graph-Based, Black-Box Approach

Jun 18, 2026 - Usability and Sustainability of Simulation Software

Neubauer, Felix, 2026, "Replication data for: Orchestrating Schema Conversions Across Heterogeneous Schema Languages: A Graph-Based, Black-Box Approach", https://doi.org/10.18419/DARUS-6158, DaRUS, V2, UNF:6:MTCchV/htouIGFqJY7cJug== [fileUNF]

This dataset accompanies the paper "Orchestrating Schema Conversions Across Heterogeneous Schema Languages: A Graph-Based, Black-Box Approach" and contains source code snapshots, evaluation inputs, and evaluation outputs for the Schema Conversion Orchestrator and its integration into the MetaConfigurator tool. The dataset includes a snapshot of the...

Data for "Anion Effects in Electrochemical Transistors with Semiconducting Single-Walled Carbon Nanotube Networks"

Jun 17, 2026 - Zaumseil group Dataverse

Xu, Xuqiang; Fresta, Elisa; Lindenthal, Sebastian; Michel, Edwin; Zaumseil, Jana, 2026, "Data for "Anion Effects in Electrochemical Transistors with Semiconducting Single-Walled Carbon Nanotube Networks"", https://doi.org/10.18419/DARUS-5338, DaRUS, V1

This dataset contains all data underlying the figures in the paper "Anion Effects in Electrochemical Transistors with Semiconducting Single-Walled Carbon Nanotube Networks" (including the supporting information). Abbreviations used in the headers of the txt-files: Id: drain current Ig: gate (leakage) current gm: transconductance L: channel length W...

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