EXC 2075 Project Networks

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1 to 10 of 253 Results

Replication Data for: Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations Jan 14, 2026 - Coarse-grained non-equilibrium dynamics with generative machine learning Egenlauf, Patrick; Březinová, Iva; Andergassen, Sabine; Klopotek, Miriam, 2026, "Replication Data for: Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations", https://doi.org/10.18419/DARUS-5613, DaRUS, V1 This dataset contains all relevant data to reproduce the results of the paper titled "Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations". It contains the exact time series data of the two-particle reduced density matrix (2RDM) for each parameter configuration of the parameter scan, with...
Optimization of magnetoelectric composites using convolutional neural networks - scripts and dataset Dec 22, 2025 - PN 3-5 Sriram, Siddharth, 2025, "Optimization of magnetoelectric composites using convolutional neural networks - scripts and dataset", https://doi.org/10.18419/DARUS-5623, DaRUS, V1 This repository is intended to host the supplementary material (dataset and scripts) associated with the article “Optimization of magnetoelectric composites using convolutional neural networks”. The HDF5 file 'Microstructure_data.h5' contains the dataset of microstructural images and their effective properties of interest, computed using the finite...
Coarse-grained non-equilibrium dynamics with generative machine learning(Universität Stuttgart) Dec 15, 2025PN 6
Replication Data for: "BSP k-Means" Dec 11, 2025 - PN 6-4 Künzel, Sebastian; Weiskopf, Daniel, 2025, "Replication Data for: "BSP k-Means"", https://doi.org/10.18419/DARUS-5575, DaRUS, V1 This dataset contains reference implementations in C++ and CUDA for the algorithm presented in the paper "BSP k-Means". The purpose of the data is to allow replication of the reported results.
Kinetic modeling of enzymatic cephalexin synthesis with neural ODEs and surrogate-accelerated Bayesian inference Dec 9, 2025 - PN 2-6 Range, Jan Peter; Pleiss, Jürgen; Bommarius, Andreas, 2025, "Kinetic modeling of enzymatic cephalexin synthesis with neural ODEs and surrogate-accelerated Bayesian inference", https://doi.org/10.18419/DARUS-5539, DaRUS, V1, UNF:6:l47sIu5Gd2e6cn3HDM5h6g== [fileUNF] α-Amino ester hydrolases (AEHs) offer a promising route to the stereoselective synthesis of β-lactams such as cephalexin. However, published kinetic studies have encountered difficulty when extended beyond fitting of the data, indicating practical non-identifiability of the underlying kinetic models. Here, we address this issue using Bayesian infer...
Replication Code for: Augmenting a pure and hybrid vertical equilibrium scheme via data-driven surrogate modelling Dec 1, 2025 - PN 5-2 (II) Buntic, Ivan; Flemisch, Bernd, 2025, "Replication Code for: Augmenting a pure and hybrid vertical equilibrium scheme via data-driven surrogate modelling", https://doi.org/10.18419/DARUS-5343, DaRUS, V2 This data set contains the source code to reproduce the simulation and data-driven models for the publication Augmenting a pure and hybrid vertical me via data-driven surrogate modelling, that has been submitted to the Transport in Porous Media journal. Files README.md: Instructions on installing all necessary modules using git or Docker. install_b...
Supplementary Data for: Phase Diagram and Criticality of the Modified Primitive Electrolyte Model in Bulk and Inert and Conducting Confinement Nov 28, 2025 - PN 3 Stärk, Philipp; Schlaich, Alexander, 2025, "Supplementary Data for: Phase Diagram and Criticality of the Modified Primitive Electrolyte Model in Bulk and Inert and Conducting Confinement", https://doi.org/10.18419/DARUS-5037, DaRUS, V1, UNF:6:2rxz9p/7+PzWplE3Nv/71A== [fileUNF] Supplementary Data for: Phase Diagram and Criticality of the Modified Primitive Electrolyte Model in Bulk and Inert and Conducting Confinement This data respository contains software code for an implementation of the Wang-Landau (WL) method in LAMMPS, code to "stitch" together free energy profiles from WL runs of sub-spaces of the phase space, simu...
Replication Data for: A Modular Approach for Mesh-Particle Coupling Nov 26, 2025 - Usability and Sustainability of Simulation Software Schneider, David, 2025, "Replication Data for: A Modular Approach for Mesh-Particle Coupling", https://doi.org/10.18419/DARUS-5494, DaRUS, V1 This dataset contains software as well as setup and result files to reproduce the numerical experiments in Chapter 7 of my dissertation titled "Flexible and Efficient Data Mapping for Simulation of Coupled Problems". For further instructions on how to run the experiments see the README.md of the dataset.
Supplementary Data for: Static Dielectric Profiles and Coarse-graining Approaches for Water in Graphene Slit Pores: The Crucial Influence of Boundary Conditions in Simulations Nov 25, 2025 - PN 3 Stärk, Philipp; Stooß, Henrik; Loche, Philip; Bonthuis, Douwe Jan; Netz, Roland; Schlaich, Alexander, 2025, "Supplementary Data for: Static Dielectric Profiles and Coarse-graining Approaches for Water in Graphene Slit Pores: The Crucial Influence of Boundary Conditions in Simulations", https://doi.org/10.18419/DARUS-4317, DaRUS, V1 This repository contains the input scripts and raw data to replicate the results of the main publication.
Atmospyre v1.0.0 Nov 17, 2025 - PN 1-X Keim, Leon, 2025, "Atmospyre v1.0.0", https://doi.org/10.18419/DARUS-5531, DaRUS, V1 Release v1.0.0 of AtmosPyre. AtmosPyre is a flexible library for atmospheric measurements. Monitor CO₂, Radon, and more with an intuitive Python API.

Replication Data for: Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations

Jan 14, 2026 - Coarse-grained non-equilibrium dynamics with generative machine learning

Egenlauf, Patrick; Březinová, Iva; Andergassen, Sabine; Klopotek, Miriam, 2026, "Replication Data for: Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations", https://doi.org/10.18419/DARUS-5613, DaRUS, V1

This dataset contains all relevant data to reproduce the results of the paper titled "Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations". It contains the exact time series data of the two-particle reduced density matrix (2RDM) for each parameter configuration of the parameter scan, with...

Optimization of magnetoelectric composites using convolutional neural networks - scripts and dataset

Dec 22, 2025 - PN 3-5

Sriram, Siddharth, 2025, "Optimization of magnetoelectric composites using convolutional neural networks - scripts and dataset", https://doi.org/10.18419/DARUS-5623, DaRUS, V1

This repository is intended to host the supplementary material (dataset and scripts) associated with the article “Optimization of magnetoelectric composites using convolutional neural networks”. The HDF5 file 'Microstructure_data.h5' contains the dataset of microstructural images and their effective properties of interest, computed using the finite...

Coarse-grained non-equilibrium dynamics with generative machine learning(Universität Stuttgart)

Dec 15, 2025PN 6

Replication Data for: "BSP k-Means"

Dec 11, 2025 - PN 6-4

Künzel, Sebastian; Weiskopf, Daniel, 2025, "Replication Data for: "BSP k-Means"", https://doi.org/10.18419/DARUS-5575, DaRUS, V1

This dataset contains reference implementations in C++ and CUDA for the algorithm presented in the paper "BSP k-Means". The purpose of the data is to allow replication of the reported results.

Kinetic modeling of enzymatic cephalexin synthesis with neural ODEs and surrogate-accelerated Bayesian inference

Dec 9, 2025 - PN 2-6

Range, Jan Peter; Pleiss, Jürgen; Bommarius, Andreas, 2025, "Kinetic modeling of enzymatic cephalexin synthesis with neural ODEs and surrogate-accelerated Bayesian inference", https://doi.org/10.18419/DARUS-5539, DaRUS, V1, UNF:6:l47sIu5Gd2e6cn3HDM5h6g== [fileUNF]

α-Amino ester hydrolases (AEHs) offer a promising route to the stereoselective synthesis of β-lactams such as cephalexin. However, published kinetic studies have encountered difficulty when extended beyond fitting of the data, indicating practical non-identifiability of the underlying kinetic models. Here, we address this issue using Bayesian infer...

Replication Code for: Augmenting a pure and hybrid vertical equilibrium scheme via data-driven surrogate modelling

Dec 1, 2025 - PN 5-2 (II)

Buntic, Ivan; Flemisch, Bernd, 2025, "Replication Code for: Augmenting a pure and hybrid vertical equilibrium scheme via data-driven surrogate modelling", https://doi.org/10.18419/DARUS-5343, DaRUS, V2

This data set contains the source code to reproduce the simulation and data-driven models for the publication Augmenting a pure and hybrid vertical me via data-driven surrogate modelling, that has been submitted to the Transport in Porous Media journal. Files README.md: Instructions on installing all necessary modules using git or Docker. install_b...

Supplementary Data for: Phase Diagram and Criticality of the Modified Primitive Electrolyte Model in Bulk and Inert and Conducting Confinement

Nov 28, 2025 - PN 3

Stärk, Philipp; Schlaich, Alexander, 2025, "Supplementary Data for: Phase Diagram and Criticality of the Modified Primitive Electrolyte Model in Bulk and Inert and Conducting Confinement", https://doi.org/10.18419/DARUS-5037, DaRUS, V1, UNF:6:2rxz9p/7+PzWplE3Nv/71A== [fileUNF]

Supplementary Data for: Phase Diagram and Criticality of the Modified Primitive Electrolyte Model in Bulk and Inert and Conducting Confinement This data respository contains software code for an implementation of the Wang-Landau (WL) method in LAMMPS, code to "stitch" together free energy profiles from WL runs of sub-spaces of the phase space, simu...

Replication Data for: A Modular Approach for Mesh-Particle Coupling

Nov 26, 2025 - Usability and Sustainability of Simulation Software

Schneider, David, 2025, "Replication Data for: A Modular Approach for Mesh-Particle Coupling", https://doi.org/10.18419/DARUS-5494, DaRUS, V1

This dataset contains software as well as setup and result files to reproduce the numerical experiments in Chapter 7 of my dissertation titled "Flexible and Efficient Data Mapping for Simulation of Coupled Problems". For further instructions on how to run the experiments see the README.md of the dataset.

Supplementary Data for: Static Dielectric Profiles and Coarse-graining Approaches for Water in Graphene Slit Pores: The Crucial Influence of Boundary Conditions in Simulations

Nov 25, 2025 - PN 3

Stärk, Philipp; Stooß, Henrik; Loche, Philip; Bonthuis, Douwe Jan; Netz, Roland; Schlaich, Alexander, 2025, "Supplementary Data for: Static Dielectric Profiles and Coarse-graining Approaches for Water in Graphene Slit Pores: The Crucial Influence of Boundary Conditions in Simulations", https://doi.org/10.18419/DARUS-4317, DaRUS, V1

This repository contains the input scripts and raw data to replicate the results of the main publication.

Atmospyre v1.0.0

Nov 17, 2025 - PN 1-X

Keim, Leon, 2025, "Atmospyre v1.0.0", https://doi.org/10.18419/DARUS-5531, DaRUS, V1

Release v1.0.0 of AtmosPyre. AtmosPyre is a flexible library for atmospheric measurements. Monitor CO₂, Radon, and more with an intuitive Python API.

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