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1 to 10 of 35 Results
Jun 24, 2021 - CAMPOS Project P8: Conceptual Model Uncertainty
Gonzalez-Nicolas Alvarez, Ana, 2021, "Sampling Strategies of the Regime-and-memory model (RMM)", https://doi.org/10.18419/darus-2035, DaRUS, V1, UNF:6:JeAvfovoq369qtbASSmQjg== [fileUNF]
This excel file includes the observation time, Q, concentration, and lag-time used by the sampling strategies. Types of sampling strategies: Time frequency sampling strategies. River discharge frequency sampling strategies. Low Q sampling strategies. High Q sampling strategies. L...
Jun 24, 2021 - CAMPOS Project P8: Conceptual Model Uncertainty
Gonzalez-Nicolas Alvarez, Ana, 2021, "Regime-and-memory model (RMM) Code", https://doi.org/10.18419/darus-2034, DaRUS, V1
We introduce a simple stochastic time-series model (regime-and-memory model, RMM) for concentrations in the river that accounts for fluctuating release and transport with memory, using an autocorrelation over time.One explicit parameter of our model represents the export regime....
Jun 18, 2021 - Modeling Strategies for Gas migration in Subsurface
Banerjee, Ishani, 2021, "Replication Data for: Overcoming the model-data-fit problem in porous media: A quantitative method to compare invasion-percolation models to high-resolution data", https://doi.org/10.18419/darus-1776, DaRUS, V1
This dataset contains modeling data used to obtain the results and figures in the manuscript: "Overcoming the model-data-fit problem in porous media: A quantitative method to compare invasion-percolation models to high-resolution data." In particular, the model realization data a...
Computational Cognitive Science(Universität Stuttgart)
Jun 15, 2021PN 7
Data collections by the Stuttgart CCS group, mostly Encephalography, Eye-Tracking and human behavior data.
May 26, 2021 - PN 6-4
Munz, Tanja; Väth, Dirk; Kuznecov, Paul; Vu, Ngoc Thang; Weiskopf, Daniel, 2021, "NMTVis - Trained Models for our Visual Analytics System", https://doi.org/10.18419/darus-1850, DaRUS, V1
Trained models and vocabulary files for the use in our visual analytics system NMTVis. There are models for German to English and vice versa available for an LSTM-based and the Transformer architecture.
May 26, 2021 - PN 6-4
Munz, Tanja; Väth, Dirk; Kuznecov, Paul; Vu, Ngoc Thang; Weiskopf, Daniel, 2021, "NMTVis - Neural Machine Translation Visualization System", https://doi.org/10.18419/darus-1849, DaRUS, V1
NMTVis is a web-based visual analytics system to analyze, understand, and correct translations generated with neural machine translation. First, a document can be translated using a neural machine translation model (we support an LSTM-based and the Transformer architecture). Afte...
May 21, 2021 - PN 4-4
Eschmann, Hannes, 2021, "A Data Set for Research on Data-based Methods for an Omnidirectional Mobile Robot", https://doi.org/10.18419/darus-1845, DaRUS, V1
The intend of this data set is the cooperation within SimTech. It will be particularly interesting for data-based modeling and control which is a key area of the research of project network 4. We are proud to provide real-world data, which is essential for the benchmark of any da...
PN 4-4(Institute of Engineering and Computational Mechanics, Universität Stuttgart)
May 10, 2021PN 4
Bridging the gap between theoretic research in distributed and learning-based model predictive control and multi-agent applications.
Mar 23, 2021 - PN 6-3
Holzmüller, David, 2021, "Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression", https://doi.org/10.18419/darus-1771, DaRUS, V1
This dataset contains code used to generate the figures in the paper On the Universality of the Double Descent Peak in Ridgeless Regression, David Holzmüller, International Conference on Learning Representations 2021. The code is also provided on GitHub. Here, we additionally pro...
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