1 to 10 of 41 Results
May 28, 2025 - PN 6-8 (II)
Bauer, Ruben; Evers, Marina; Quang Ngo, Quynh; Reina, Guido; Frey, Steffen; Sedlmair, Michael, 2025, "Replication data for: Voronoi Cell Interface-Based Parameter Sensitivity Analysis for Labeled Samples", https://doi.org/10.18419/DARUS-4930, DaRUS, V1, UNF:6:3NivtJY91pyT7tXMB/YrJQ== [fileUNF]
This dataset contains the data and code for the publication: Voronoi Cell Interface-Based Parameter Sensitivity Analysis for Labeled Samples. Code Repository A dynamic version of the code repository can be found at https://github.com/rbnbr/VoroParaSense. The version presented in this dataset corresponds to the version used in the corresponding pape... |
May 28, 2025 - PN 6-4
Schäfer, Noel; Künzel, Sebastian; Tilli, Pascal; Munz-Körner, Tanja; Vidyapu, Sandeep; Vu, Ngoc Thang; Weiskopf, Daniel, 2025, "Extended Visual Analysis System for Scene-Graph-Based Visual Question Answering", https://doi.org/10.18419/DARUS-3909, DaRUS, V1
Source code of our extended visual analysis system to explore scene-graph-based visual question answering. This approach is built on top of the state-of-the-art GraphVQA framework which was trained on the GQA dataset. Additionally, it is an improved version of our system that can be found here Instructions on how to use our system can be found in t... |
May 12, 2025 - PN 6-15
Gaimann, Mario U.; Klopotek, Miriam, 2025, "Supplementary Videos for: Robustly optimal dynamics for active matter reservoir computing (Gaimann and Klopotek, 2025)", https://doi.org/10.18419/DARUS-4619, DaRUS, V1
This dataset contains supplementary videos for the publication "Robustly optimal dynamics for active matter reservoir computing" (Gaimann and Klopotek, 2025) The videos show active matter systems (swarms) driven by an external force. These swarm systems can be used to predict the future trajectory of the external driving force using reservoir compu... |
May 12, 2025 - PN 6-15
Gaimann, Mario U.; Klopotek, Miriam, 2025, "Replication Data for: Robustly optimal dynamics for active matter reservoir computing (Gaimann and Klopotek, 2025)", https://doi.org/10.18419/DARUS-4620, DaRUS, V1, UNF:6:JR70RsK1jeEUWlriMxeIpw== [fileUNF]
This repository contains raw and post-processed replication data for the publication "Robustly optimal dynamics 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 force. These simulations se... |
Apr 9, 2025 - PN 6A-4
Álvarez Chaves, Manuel, 2025, "Replication Data for: An entropy-based evaluation of conceptual constraints in hybrid hydrological models", https://doi.org/10.18419/DARUS-4920, DaRUS, V1, UNF:6:i3yM0uireOQetNHaTVPKfg== [fileUNF]
Hybrid Models for Hydrology This repository contains code for the paper "When physics gets in the way: an entropy-based evaluation of conceptual constraints in hybrid hydrological models" submitted to Hydrology and Earth Systems Science (HESS). In this repository we have included the 'Hy2DL' and 'unite_toolbox' libraries in the versions they used f... |
Mar 28, 2025
Spatiotemporal ensembles often result from physical simulations. These ensembles contain many information-rich members, each corresponding to different simulation input parameters. The extensive data size makes manual analysis infeasible, necessitating automated approaches to assist the analysis. In the preceding project (PN 6-8 (I)), methods and t... |
Nov 20, 2024
This Dataverse contains replication data and visualizations from Project Network 6-15: Machine Learning and Reservoir Computing with Many-Body Dynamics. The project is part of SimTech’s Project Network 6, Machine Learning for Simulation (https://www.simtech.uni-stuttgart.de/exc/research/pn/pn6/ ). The Dataverse includes simulations of non-equilibri... |
Nov 5, 2024 - PN 6-3
Holzmüller, David; Grinsztajn, Léo; Steinwart, Ingo, 2024, "Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data [NeurIPS, arXiv v2]", https://doi.org/10.18419/DARUS-4555, DaRUS, V1
This dataset contains code and data for our paper "Better by default: Strong pre-tuned MLPs and boosted trees on tabular data", specifically, the NeurIPS version which is also the second version on arXiv. The main code is provided in pytabkit_code.zip and contains further documentation in README.md and the docs folder. The main code is also provide... |
Aug 8, 2024 - PN 6-3
Holzmüller, David; Grinsztajn, Léo; Steinwart, Ingo, 2024, "Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data", https://doi.org/10.18419/DARUS-4255, DaRUS, V1
This dataset contains code and data for our paper "Better by default: Strong pre-tuned MLPs and boosted trees on tabular data". The main code is provided in pytabkit_code.zip and contains further documentation in README.md and the docs folder. The main code is also provided on GitHub. Here, we additionally provide the data that is generated by the... |
Jul 8, 2024 - Hard Negative Captions
Tilli, Pascal, 2024, "Data for: HNC: Leveraging Hard Negative Captions towards Models with Fine-Grained Visual-Linguistic Comprehension Capabilities", https://doi.org/10.18419/DARUS-4341, DaRUS, V1
Image-Text-Matching (ITM) is one of the defacto methods of learning generalized representations from a large corpus in Vision and Language (VL). However, due to the weak association between the web-collected image–text pairs, models fail to show fine-grained understanding of the combined semantics of these modalities. To this end, we propose Hard N... |
