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61 to 70 of 276 Results
Oct 28, 2022 - Collaborative Artificial Intelligence
Bulling, Andreas, 2022, "Data for Recognition of Visual Memory Recall Processes Using Eye Movement Analysis", https://doi.org/10.18419/DARUS-3225, DaRUS, V1
This dataset was recorded to investigate the feasibility of recognising visual memory recall from eye movements. Eye movement data was recorded of participants looking at familiar and unfamiliar pictures from four picture categories: abstract, landscapes, faces, and buildings. The study was designed with two objectives in mind: (1) to elicit distin...
DuMux(Universität Stuttgart)
DuMux logo
Oct 27, 2022Hydromechanics and Modelling of Hydrosystems
DuMux, https://dumux.org/, is short for Dune for Multi-{Phase, Component, Scale, Physics, …} flow and transport in porous media a free and open-source simulator for flow and transport processes in porous media a research code written in C++ based on Dune (Distributed and Unified Numerics Environment), https://dune-project.org/ a Dune user module in...
Oct 27, 2022Institute for Modelling Hydraulic and Environmental Systems (IWS)
The Department of Hydromechanics and Modelling of Hydrosystems is one out of five departments of the Institute for Modelling Hydraulic and Environmental Systems (IWS).
Oct 26, 2022 - Projects without PN Affiliation
Davis, Kyle; Schulte, Miriam, 2022, "Replication Data for: Geothermal-ML - predicting thermal plume from groundwater heat pumps", https://doi.org/10.18419/DARUS-3184, DaRUS, V1
This dataset provides all python3 code necessary to train convolutional neural networks built with pyTorch, as well as the data to train the networks. A README file is provided with instructions for accessing the training data, viewing the alread computed models, and all software dependency versions.
Oct 26, 2022 - Projects without PN Affiliation
Davis, Kyle; Schulte, Miriam, 2022, "COM-4 model to replicate simulation results for the GEO.KW project", https://doi.org/10.18419/DARUS-3185, DaRUS, V1
This data repository contains the COM-4 model for the GEO.KW project. The dataset contains the PFLOTRAN and urbs simulation setup, spack build environment and spack build mirror to replicate the software build environment. A README file is provided, explaining the spack building procedure and running the simulation.
Oct 26, 2022 - Projects without PN Affiliation
Davis, Kyle; Schulte, Miriam, 2022, "REG-30 model to replicate simulation results for the GEO.KW project", https://doi.org/10.18419/DARUS-3195, DaRUS, V1
This data repository contains the REG-30 model for the GEO.KW project. The dataset contains the PFLOTRAN and urbs software and simulation setup. Instructions for building the spack environment and running the simulation are provided in the README.
Oct 26, 2022 - Projects without PN Affiliation
Davis, Kyle; Schulte, Miriam, 2022, "Replication Data for: Radial basis function interpolation with partition of unity for PyRBF", https://doi.org/10.18419/DARUS-3183, DaRUS, V1, UNF:6:n9rIOI84ZodNZYhB8p26GQ== [fileUNF]
The dataset provides the PyRBF python code to perform partition of unity radial basis function interpolation. This includes all meshes in VTK format and a post processing folder to generate the figures from provided results. The README provides further instructions. All software dependency versions are provided in the README.
Oct 26, 2022 - Modeling Strategies for Gas migration in Subsurface
Banerjee, Ishani; Walter, Peter, 2022, "Replication Data for: The Method of Forced Probabilities: a Computation Trick for Bayesian Model Evidence", https://doi.org/10.18419/DARUS-2815, DaRUS, V1
This dataset contains the codes used for implementing the method of forced probabilities of the manuscript: The Method of Forced Probabilities: A Computation Trick for Bayesian Model Evidence. Here, one can find the codes of implementation of the trick on stochastic invasion percolation (SIP) models discussed in the manuscript; it can be used by th...
Materials Design(Universität Stuttgart)
Oct 24, 2022Institute for Materials Science
Institute for Materials Science(Universität Stuttgart)
Oct 24, 2022
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