EXC 2075 Project Networks

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Publication Year: 2024

1 to 10 of 13 Results

Replication Data for: Development of a framework for point-particle tracking Mar 7, 2024 - Usability and Sustainability of Simulation Software Kschidock, Helena, 2024, "Replication Data for: Development of a framework for point-particle tracking", https://doi.org/10.18419/darus-3760, DaRUS, V1 This dataset contains a custom build for Altair's simulation software ultraFluidX and the input files used in the Master Thesis 'Development of an Euler-Lagrangian framework for point-particle tracking to enable efficient multiscale simulations of complex flows', submitted by Hel...
PN 6A-4(Universität Stuttgart) Mar 8, 2024PN 6 Unified diagnostic evaluation of physics-based, data-driven and hybrid hydrological models based on information theory
PN 3A-7(Universität Stuttgart) Mar 8, 2024PN 3 Advanced Learning Strategies for Machine Learned Interatomic Potentials
PN 6A-3(Universität Stuttgart) Mar 8, 2024PN 6 Advanced learning strategies for potential energy surfaces applied to organic electrolytes
PN 1-X(Universität Stuttgart) Mar 12, 2024PN 1
PN 2-7(Universität Stuttgart) 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"
Replication Data for: On the Accurate Estimation of Information-Theoretic Quantities from Multi-Dimensional Sample Data Mar 14, 2024 - PN 6A-4 Alvarez Chaves, Manuel; Gupta, Hoshin; Ehret, Uwe; Guthke, Anneli, 2024, "Replication Data for: On the Accurate Estimation of Information-Theoretic Quantities from Multi-Dimensional Sample Data", 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: "On the Accurate Estimation of Information-Theoretic Quantities from Multi-Dimensional Sample Data". The projects is organizes as follows: ├── analysis_results\ │ ├── plots\ ├...
Replication Code for: Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference Mar 14, 2024 - PN 2-7 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.
Simulation Results from the Descriptive Graph-based Model of two Example Driving Scenarios Mar 28, 2024 - PN 7-6 Bechler, Florian, 2024, "Simulation Results from the Descriptive Graph-based Model of two Example Driving Scenarios", https://doi.org/10.18419/darus-4116, DaRUS, V1 Video of the interior and exterior information of a driving scenario, with the resulting graph-based description. The video shows a combination of exterior data of a driving scenario in combination with information about the drivers eyegaze. On the right side a resulting graph-ba...
Replication Code for: Rayleigh invariance allows the estimation of effective CO2 fluxes due to convective dissolution into water-filled fractures $Replication Code for: Rayleigh invariance allows the estimation of effective CO2 fluxes due to convective dissolution into water-filled fractures$ Apr 18, 2024 - PN 1-X 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...

Replication Data for: Development of a framework for point-particle tracking

Mar 7, 2024 - Usability and Sustainability of Simulation Software

Kschidock, Helena, 2024, "Replication Data for: Development of a framework for point-particle tracking", https://doi.org/10.18419/darus-3760, DaRUS, V1

This dataset contains a custom build for Altair's simulation software ultraFluidX and the input files used in the Master Thesis 'Development of an Euler-Lagrangian framework for point-particle tracking to enable efficient multiscale simulations of complex flows', submitted by Hel...

PN 6A-4(Universität Stuttgart)

Mar 8, 2024PN 6

Unified diagnostic evaluation of physics-based, data-driven and hybrid hydrological models based on information theory

PN 3A-7(Universität Stuttgart)

Mar 8, 2024PN 3

Advanced Learning Strategies for Machine Learned Interatomic Potentials

PN 6A-3(Universität Stuttgart)

Mar 8, 2024PN 6

Advanced learning strategies for potential energy surfaces applied to organic electrolytes

PN 1-X(Universität Stuttgart)

Mar 12, 2024PN 1

PN 2-7(Universität Stuttgart)

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"

Replication Data for: On the Accurate Estimation of Information-Theoretic Quantities from Multi-Dimensional Sample Data

Mar 14, 2024 - PN 6A-4

Alvarez Chaves, Manuel; Gupta, Hoshin; Ehret, Uwe; Guthke, Anneli, 2024, "Replication Data for: On the Accurate Estimation of Information-Theoretic Quantities from Multi-Dimensional Sample Data", 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: "On the Accurate Estimation of Information-Theoretic Quantities from Multi-Dimensional Sample Data". The projects is organizes as follows: ├── analysis_results\ │ ├── plots\ ├...

Replication Code for: Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference

Mar 14, 2024 - PN 2-7

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.

Simulation Results from the Descriptive Graph-based Model of two Example Driving Scenarios

Mar 28, 2024 - PN 7-6

Bechler, Florian, 2024, "Simulation Results from the Descriptive Graph-based Model of two Example Driving Scenarios", https://doi.org/10.18419/darus-4116, DaRUS, V1

Video of the interior and exterior information of a driving scenario, with the resulting graph-based description. The video shows a combination of exterior data of a driving scenario in combination with information about the drivers eyegaze. On the right side a resulting graph-ba...

Replication Code for: Rayleigh invariance allows the estimation of effective CO2 fluxes due to convective dissolution into water-filled fractures

$Replication Code for: Rayleigh invariance allows the estimation of effective CO2 fluxes due to convective dissolution into water-filled fractures$

Apr 18, 2024 - PN 1-X

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...

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