Find research datasets worth reusing
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6
datasets available to search
ShareScore release 0.9.0
Dataset results
6 results for “reduced-order models”
Data for "Reduced-Order Biogeochemical Flux Model for Upper OceanBiophysical Simulations"
<p>Data, figure generation scripts, and zero-dimensional version of the 17 species Biogeochemical Flux Model (BFM17) for the paper "Reduced-Order Biogeochemical Flux Model for Upper OceanBiophysical Simulations" submitted to Geoscientific Model Development. </p>
Datasets of paper "Improving the performance of a reduced-order mass-consistent model for urban environments and complex terrain with a higher-order geometrical representation"
<p>These are the datasets, processing scripts, and plots that are used in the paper titled "Improving the performance of a reduced-order mass-consistent model for urban environments and complex terrain with a higher-order geometrical representation" submitted to the JAMES.</p>
Data in support of Plume Dynamics Reduced-Order Models
<p>This split tarball contains the data used in experiments in the paper "Coarse Graining and Reduced Order Models for Plume Dynamics". Unzipping the tarball in the experiment repository, or symlinking from the repository to the unzipped directory "plume_videos", will allow experiments to run.</p> <p>Data is laid out as it is in our machine. This includes movie files, numpy arrays of movies, and pickled coordinates of plume origins. </p> <p>Tarball is fragmented using the unix split command. Run `cat x* | tar -xzvf -`. See https://unix.stackexchange.com/questions/61774/create-a-tar-archive-split-into-blocks-of-a-maximum-size</p>
Multi-fidelity reduced-order surrogate modeling
<p>Training and testing datasets used for the experiments in <a href="https://arxiv.org/abs/2309.00325">Multi-fidelity reduced-order surrogate modeling</a></p>
Data from the thesis: Reduced-order models to predict mesoscale mechanical behavior of polycrystalline materials
<p>This record contains the data and code from the thesis: Reduced-order models to predict mesoscale mechanical behavior of polycrystalline materials. The contents of the chapter-wise zip files are described in the respective markdown files with the suffix <strong><em>_readme.md</em></strong>.</p> <p> </p> <p>A record containing only the code from the thesis is availabe at: <a href="https://doi.org/10.5281/zenodo.10983507" target="_blank" rel="noopener">10.5281/zenodo.10983507</a>.</p>
Reduced-Order Model of Time-Projection Chamber
<p>These datasets are generated by a <strong>reduced-order model (ROM) of the sPHENIX Time-projection chamber (TPC)</strong>, inner layer group. We have two datasets:</p> <ol> <li>`dataset.zip` and</li> <li>`dataset_with_label.zip`.</li> </ol> <p>Each dataset contains 8000 training examples and 2000 test examples. Each sample in the dataset contains ~50 to 100 trajectories. Samples in both dataset contain fields: `response`, `tracks`, and `params `. Samples in the `dataset_with_label.zip` has an additional field `label`. </p> <p>Here are the description of fields:</p> <ul> <li>`response` (shared): float tensor of shape (16, 256, 1152) in radial (layer), axial (horizontal), and azimuthal directions. </li> <li>`tracks` (shared): float tensor of shape (N, 2, 16), where N is the number of trajectories. Each trajectory is recorded as a tensor of shape (2, 16). The two numbers for each layer (last axis) is the angle (in the azimuthal direction) and axial location of the trajectory. </li> <li>`params` (shared): float tensor of shape (N, 4). The four numbers for the n-th entry are initial momentum (3D) and mass-charge ratio (scalar) of the particle that generates the n-th trajectory.</li> <li>`label` (`dataset_with_label` only): integer tensor of shape (16, 256, 1152), the value for voxels <strong>with positive response</strong> is the trajectory id that contribute the most to the voxel. The value for voxels with zero response is random and should not be used.</li> </ul>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.