Stuttgart Center for Simulation Science (SC SimTech)

EXC 2075 Project Networks

SIGDIUS

Projects without PN Affiliation

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19,981 to 19,990 of 25,729 Results

single-muscle.tar.xz Feb 26, 2024 - Replication Data for: Coupled Simulations and Parameter Inversion for Neural System and Electrophysiological Muscle Models XZ Archive - 772.3 KB - MD5: 80ff9850ba0dbc8680f4687c39c944d8
Modelling, Simulation and Optimization for Agonist-Antagonist Myoneural Interface Surgeries(Universität Stuttgart) Feb 22, 2024Projects without PN Affiliation The AMI is a limb amputation technique which aims to maintain the mechanical and neural feedback between agonist and antagonist muscle. We aim to develop a platform for in silico analysis which can provide insight to surgeons. For that we combine detailed multi-physics multi-scale simulations with surrogate models for optimization.
Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes Feb 16, 2024 - PN3-5 Sriram, Siddharth, 2024, "Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes", https://doi.org/10.18419/DARUS-3881, DaRUS, V1 The datasets and codes provided here are associated with our article entitled "Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle". The main idea of the work is to develop surrogate models using the concepts of machine learning (ML) to predict the onset of wrinkling insta...
binary_classification.ipynb Feb 16, 2024 - Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes Jupyter Notebook - 13.7 KB - MD5: dacad485cece6350acf08afa30461e19
de_instabilities.yml Feb 16, 2024 - Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes application/x-yaml - 8.5 KB - MD5: 86f5d2848b4668165c8e936214efed7f
multiclass_classification.ipynb Feb 16, 2024 - Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes Jupyter Notebook - 17.6 KB - MD5: 060c1d1f671f506010836b1ef8333a41
regression.ipynb Feb 16, 2024 - Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes Jupyter Notebook - 12.2 KB - MD5: e489576c86ed8d8a49cfd1ddce73b94e
test_data.xlsx Feb 16, 2024 - Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes MS Excel Spreadsheet - 10.8 KB - MD5: 38d6ddfd9c95816f04ff36fe609c892a
training_set.xlsx Feb 16, 2024 - Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes MS Excel Spreadsheet - 49.1 KB - MD5: 6c91bdf877156aef53f78d71f7183601
PDEBench Datasets Feb 13, 2024 - SciML PDE Benchmark 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 This dataset contains benchmark data, generated with numerical simulation based on different PDEs, namely 1D advection, 1D Burgers', 1D and 2D diffusion-reaction, 1D diffusion-sorption, 1D, 2D, and 3D compressible Navier-Stokes, 2D Darcy flow, and 2D shallow water equation. This dataset is intended to progress the scientific ML research area. In ge...

single-muscle.tar.xz

Feb 26, 2024 - Replication Data for: Coupled Simulations and Parameter Inversion for Neural System and Electrophysiological Muscle Models

XZ Archive - 772.3 KB -

Modelling, Simulation and Optimization for Agonist-Antagonist Myoneural Interface Surgeries(Universität Stuttgart)

Feb 22, 2024Projects without PN Affiliation

The AMI is a limb amputation technique which aims to maintain the mechanical and neural feedback between agonist and antagonist muscle. We aim to develop a platform for in silico analysis which can provide insight to surgeons. For that we combine detailed multi-physics multi-scale simulations with surrogate models for optimization.

Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes

Feb 16, 2024 - PN3-5

Sriram, Siddharth, 2024, "Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes", https://doi.org/10.18419/DARUS-3881, DaRUS, V1

The datasets and codes provided here are associated with our article entitled "Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle". The main idea of the work is to develop surrogate models using the concepts of machine learning (ML) to predict the onset of wrinkling insta...

binary_classification.ipynb

Feb 16, 2024 - Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes

Jupyter Notebook - 13.7 KB -

de_instabilities.yml

Feb 16, 2024 - Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes

application/x-yaml - 8.5 KB -

multiclass_classification.ipynb

Feb 16, 2024 - Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes

Jupyter Notebook - 17.6 KB -

regression.ipynb

Feb 16, 2024 - Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes

Jupyter Notebook - 12.2 KB -

test_data.xlsx

Feb 16, 2024 - Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes

MS Excel Spreadsheet - 10.8 KB -

training_set.xlsx

Feb 16, 2024 - Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes

MS Excel Spreadsheet - 49.1 KB -

PDEBench Datasets

Feb 13, 2024 - SciML PDE Benchmark

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

This dataset contains benchmark data, generated with numerical simulation based on different PDEs, namely 1D advection, 1D Burgers', 1D and 2D diffusion-reaction, 1D diffusion-sorption, 1D, 2D, and 3D compressible Navier-Stokes, 2D Darcy flow, and 2D shallow water equation. This dataset is intended to progress the scientific ML research area. In ge...

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