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1,549 results for “benchmarks”
Repository of posterior distributions from Bayesian benchmark dose analysis
<p>This repository contains posterior distributions for all model parameters obtained from analysis of continuous dose-response studies.</p>
Unfair Inequality in Education: A Benchmark for AI-Fairness Research (Aequitas WP7 Use Case S2)
<h1>Unfair Inequality in Education: A Benchmark for AI-Fairness Research</h1> <p>This dataset proposes a novel benchmark specifically designed for AI fairness research in education. It can be used for challenging tasks aimed at improving students' performance and reducing dropout rates which are also discussed in the paper to emphasize significant research directions. By prioritizing fairness, this benchmark aims to foster the development of bias-free AI solutions, promoting equal educational access and outcomes for all students.</p> <h2>Structure</h2> <p><code>benchmark</code> contains:</p> <ul> <li>the proposed dataset (<code>dataset.csv</code>), </li> <li>the mask for dealing with missing values (<code>missing_mask.csv</code>), and</li> <li> <div> <div>the meta-columns providing grouping criteria and sample weights for each student (<code>meta_cols.csv</code>).</div> </div> </li> </ul> <p><code>raw_data</code> includes:</p> <ul> <li>the original dataset (<code>original.csv</code>), and</li> <li>the intermediate stages of the pre-processing and validation pipelines (<code>split</code>, <code>pre_processed</code>, and <code>validation</code>).</li> </ul> <p><code>res</code> contains the documentation, including:</p> <ul> <li>the transformation mapping each column of the original dataset to the proposed one, along with the missingness category and original text (<code>meta_data_mapping.csv</code>),</li> <li>the value type and domains of each column of the proposed datasets (<code>meta_data_stats.json</code>), and</li> <li> <div> <div>the statistical indices of the validation pipeline (<code>bias_preservation_results.json</code>).</div> </div> </li> </ul> <p><code>src</code> contains the source code for running the pre-processing and corresponding analysis:</p> <ul> <li><code>pre_processing</code> and <code>stats</code>contain the code for the two corresponding tasks, and</li> <li><code>pre_processing.py</code> and <code>split.py</code> are two entry points.</li> </ul> <p>Finally, <code>Dockerfile</code> and <code>requirements.txt</code> set up the environment for running the applications across multiple platforms and with Python, respectively.</p>
MatSim Dataset and benchmark for one-shot visual materials and textures recognition
<p><strong>The MatSim Dataset and benchmark</strong></p> <p>Synthetic dataset and real images benchmark for visual similarity recognition of materials and textures.</p> <p>MatSim: a synthetic dataset, a benchmark, and a method for computer vision-based recognition of similarities and transitions between materials and textures focusing on identifying any material under any conditions using one or a few examples (one-shot learning).</p> <p>Based on the paper: <a href="https://arxiv.org/pdf/2212.00648.pdf">One-shot recognition of any material anywhere using contrastive learning with physics-based rendering</a></p> <p> </p> <p><strong>Benchmark_MATSIM.zip: </strong>contain the benchmark made of real-world images as described in the paper</p> <p><strong>Dataset Generation Scripts.zip: </strong>Contain the Blender (4.1) Python scripts used for generating the dataset<br><br><a href="https://zenodo.org/record/7390166/files/MatSim_object_train_split_1.zip?download=1"><strong>MatSim_object_train_split_1,2,3....zip:</strong> </a>Contain a subset of the synthetics dataset for images of CGI images materials on random objects as described in the paper.</p> <p><strong>MatSimTrainObjectsNearField_.zip </strong>Contain train sets with near fieldlight sources</p> <p><strong><a href="https://zenodo.org/record/7390166/files/MatSim_Vessels_Train_1.zip?download=1">MatSim_Vessels_Train_1,2,3....zip </a></strong><a href="https://zenodo.org/api/files/020f90b2-7c41-44ad-86e3-69257884a569/MatSim_object_train_split_1.zip"><strong>:</strong> </a>Contain a subset of the synthetics dataset for images of CGI images materials inside transparent containers as described in the paper.<br><br><strong>*Note: these are subsets of the dataset; the full dataset can be found at:</strong><br><a href="https://e1.pcloud.link/publink/show?code=kZIiSQZCYU5M4HOvnQykql9jxF4h0KiC5MX">https://e1.pcloud.link/publink/show?code=kZIiSQZCYU5M4HOvnQykql9jxF4h0KiC5MX</a></p> <p>or<br><a href="https://icedrive.net/s/A13FWzZ8V2aP9T4ufGQ1N3fBZxDF">https://icedrive.net/s/A13FWzZ8V2aP9T4ufGQ1N3fBZxDF</a></p> <p> </p>
Underlying and Extended Data for Refined and benchmarked homemade media for cost-effective, weekend-free human pluripotent stem cell culture
<p>Extended Data and raw data for the manuscript "Refined home-brew media for cost-effective, weekend-free hiPSC culture and genetic engineering"</p> <p> </p> <p dir="ltr">Extended Data 1.zip - protocol for preparation of the supplement for hE8 and B8+ media</p> <p dir="ltr">Extended Data 2.zip - Gene counts, supporting files, and output results of bulk analyses</p> <p dir="ltr">Extended Data 3.zip - Images of iPS cells adapted to cE8, hE8 and B8+ taken 24, 48 and 72 hours after passage. Contains raw .tiff files for each image and a .pdf with a compiled figure</p> <p dir="ltr">Extended Data 4.zip - Results of miloR analysis on the differences in the distribution of cells adapted to cE8, hE8 and B8+ to assigned monocle clusters </p> <p dir="ltr">Manuscript Data.zip – Raw data underlying the Figures 1, 2, 4, 5, 6 and 7.</p> <p>Bulk_RNA_seq_archive – archived source code used for generating results in Figure 3</p>
PheKnowLator Human Disease KG Benchmarks: Instance-Inverse Relations-OWLNETS (v2.1.0 - May 2021)
<p><strong>PKT Human Disease Knowledge Graph Benchmark Builds (v2.1.0)</strong></p><p><strong>Build Type: </strong><i>Instance-Inverse Relations-OWLNETS</i></p><p><strong>Build Date: </strong>May 01, 2021</p><p> </p><h3><strong>Important Build Information</strong></h3><p>The benchmarks were originally built and stored using Google Cloud Platform (GCP) resources. For details and a complete description of this process, can be found on GitHub (<a href="https://github.com/callahantiff/PheKnowLator/tree/master/builds#readme">here</a>). Note that we have developed an archive for the builds on Zenodo. While the original GCP resources contained all associated files, due to the file size upload limits associated with each archive, we have limited the uploaded files to the KGs, associated metadata, and log files. The list of resources, including their URLs, and date of download, can all be found in the associated logs.</p><p>Details on each of the files generated by the build process can be found in the file associated with this directory (<a href="https://zenodo.org/records/10065431/files/PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx?download=1">PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx</a>).</p><p> </p><p>🚨 <strong>AVAILABLE FILES </strong>🚨 </p><ul><li>Available KG benchmark files are zipped and listed below.</li><li>For additional details on what each file contains, please see the associated Wiki page 👉 <a href="https://github.com/callahantiff/PheKnowLator/wiki/May-01%2C-2021">here</a>.</li></ul>
PheKnowLator Human Disease KG Benchmarks: Instance-Standard Relations-OWLNETS (v2.1.0 - May 2021)
<p><strong>PKT Human Disease Knowledge Graph Benchmark Builds (v2.1.0)</strong></p><p><strong>Build Type: </strong><i>Instance-Standard Relations-OWLNETS</i></p><p><strong>Build Date: </strong>May 01, 2021</p><p> </p><h3><strong>Important Build Information</strong></h3><p>The benchmarks were originally built and stored using Google Cloud Platform (GCP) resources. For details and a complete description of this process, can be found on GitHub (<a href="https://github.com/callahantiff/PheKnowLator/tree/master/builds#readme">here</a>). Note that we have developed an archive for the builds on Zenodo. While the original GCP resources contained all associated files, due to the file size upload limits associated with each archive, we have limited the uploaded files to the KGs, associated metadata, and log files. The list of resources, including their URLs, and date of download, can all be found in the associated logs.</p><p>Details on each of the files generated by the build process can be found in the file associated with this directory (<a href="https://zenodo.org/records/10065431/files/PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx?download=1">PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx</a>).</p><p> </p><p>🚨 <strong>AVAILABLE FILES </strong>🚨 </p><ul><li>Available KG benchmark files are zipped and listed below.</li><li>For additional details on what each file contains, please see the associated Wiki page 👉 <a href="https://github.com/callahantiff/PheKnowLator/wiki/May-01%2C-2021">here</a>.</li></ul>
PheKnowLator Human Disease KG Benchmarks: Instance-Standard Relations-OWL (v2.1.0 - May 2021)
<p><strong>PKT Human Disease Knowledge Graph Benchmark Builds (v2.1.0)</strong></p><p><strong>Build Type: </strong><i>Instance-Standard Relations-OWL</i></p><p><strong>Build Date: </strong>May 01, 2021</p><p> </p><h3><strong>Important Build Information</strong></h3><p>The benchmarks were originally built and stored using Google Cloud Platform (GCP) resources. For details and a complete description of this process, can be found on GitHub (<a href="https://github.com/callahantiff/PheKnowLator/tree/master/builds#readme">here</a>). Note that we have developed an archive for the builds on Zenodo. While the original GCP resources contained all associated files, due to the file size upload limits associated with each archive, we have limited the uploaded files to the KGs, associated metadata, and log files. The list of resources, including their URLs, and date of download, can all be found in the associated logs.</p><p>Details on each of the files generated by the build process can be found in the file associated with this directory (<a href="https://zenodo.org/records/10065431/files/PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx?download=1">PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx</a>).</p><p> </p><p>🚨 <strong>AVAILABLE FILES </strong>🚨 </p><ul><li>Available KG benchmark files are zipped and listed below.</li><li>For additional details on what each file contains, please see the associated Wiki page 👉 <a href="https://github.com/callahantiff/PheKnowLator/wiki/May-01%2C-2021">here</a>.</li></ul>
PheKnowLator Human Disease KG Benchmarks: Instance-Inverse Relations-OWL (v2.1.0 - May 2021)
<p><strong>PKT Human Disease Knowledge Graph Benchmark Builds (v2.1.0)</strong></p><p><strong>Build Type: </strong><i>Instance-Inverse Relations-OWL</i></p><p><strong>Build Date: </strong>May 01, 2021</p><p> </p><h3><strong>Important Build Information</strong></h3><p>The benchmarks were originally built and stored using Google Cloud Platform (GCP) resources. For details and a complete description of this process, can be found on GitHub (<a href="https://github.com/callahantiff/PheKnowLator/tree/master/builds#readme">here</a>). Note that we have developed an archive for the builds on Zenodo. While the original GCP resources contained all associated files, due to the file size upload limits associated with each archive, we have limited the uploaded files to the KGs, associated metadata, and log files. The list of resources, including their URLs, and date of download, can all be found in the associated logs.</p><p>Details on each of the files generated by the build process can be found in the file associated with this directory (<a href="https://zenodo.org/records/10065431/files/PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx?download=1">PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx</a>).</p><p> </p><p>🚨 <strong>AVAILABLE FILES </strong>🚨 </p><ul><li>Available KG benchmark files are zipped and listed below.</li><li>For additional details on what each file contains, please see the associated Wiki page 👉 <a href="https://github.com/callahantiff/PheKnowLator/wiki/May-01%2C-2021">here</a>.</li></ul>
PheKnowLator Human Disease KG Benchmarks: Class-Standard Relations-OWLNETS (v2.1.0 - May 2021)
<p><strong>PKT Human Disease Knowledge Graph Benchmark Builds (v2.1.0)</strong></p><p><strong>Build Type: </strong><i>Class-Standard Relations-OWLNETS</i></p><p><strong>Build Date: </strong>May 01, 2021</p><p> </p><h3><strong>Important Build Information</strong></h3><p>The benchmarks were originally built and stored using Google Cloud Platform (GCP) resources. For details and a complete description of this process, can be found on GitHub (<a href="https://github.com/callahantiff/PheKnowLator/tree/master/builds#readme">here</a>). Note that we have developed an archive for the builds on Zenodo. While the original GCP resources contained all associated files, due to the file size upload limits associated with each archive, we have limited the uploaded files to the KGs, associated metadata, and log files. The list of resources, including their URLs, and date of download, can all be found in the associated logs.</p><p>Details on each of the files generated by the build process can be found in the file associated with this directory (<a href="https://zenodo.org/records/10065431/files/PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx?download=1">PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx</a>).</p><p> </p><p>🚨 <strong>AVAILABLE FILES </strong>🚨 </p><ul><li>Available KG benchmark files are zipped and listed below.</li><li>For additional details on what each file contains, please see the associated Wiki page 👉 <a href="https://github.com/callahantiff/PheKnowLator/wiki/May-01%2C-2021">here</a>.</li></ul>
PheKnowLator Human Disease KG Benchmarks: Instance-Standard Relations-OWL (v2.0.0 - February 2021)
<p><strong>PKT Human Disease Knowledge Graph Benchmark Builds (v2.0.0)</strong></p><p><strong>Build Type: </strong><i>Instance-Standard Relations-OWL</i></p><p><strong>Build Date: </strong>February 11, 2021</p><p> </p><h3><strong>Important Build Information</strong></h3><p>The benchmarks were originally built and stored using Google Cloud Platform (GCP) resources. For details and a complete description of this process, can be found on GitHub (<a href="https://github.com/callahantiff/PheKnowLator/tree/master/builds#readme">here</a>). Note that we have developed an archive for the builds on Zenodo. While the original GCP resources contained all associated files, due to the file size upload limits associated with each archive, we have limited the uploaded files to the KGs, associated metadata, and log files. The list of resources, including their URLs, and date of download, can all be found in the associated logs.</p><p>Details on each of the files generated by the build process can be found in the file associated with this directory (<a href="https://zenodo.org/records/10065431/files/PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx?download=1">PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx</a>).</p><p> </p><p>🚨 <strong>AVAILABLE FILES </strong>🚨 </p><ul><li>Available KG benchmark files are zipped and listed below.</li><li>For additional details on what each file contains, please see the associated Wiki page 👉 <a href="https://github.com/callahantiff/PheKnowLator/wiki/February-11%2C-2021">here</a>.</li></ul>
PheKnowLator Human Disease KG Benchmarks: Instance-Standard Relations-OWLNETS (v2.0.0 - February 2021)
<p><strong>PKT Human Disease Knowledge Graph Benchmark Builds (v2.0.0)</strong></p><p><strong>Build Type: </strong><i>Class-Standard Relations-OWLNETS</i></p><p><strong>Build Date: </strong>February 11, 2021</p><p> </p><h3><strong>Important Build Information</strong></h3><p>The benchmarks were originally built and stored using Google Cloud Platform (GCP) resources. For details and a complete description of this process, can be found on GitHub (<a href="https://github.com/callahantiff/PheKnowLator/tree/master/builds#readme">here</a>). Note that we have developed an archive for the builds on Zenodo. While the original GCP resources contained all associated files, due to the file size upload limits associated with each archive, we have limited the uploaded files to the KGs, associated metadata, and log files. The list of resources, including their URLs, and date of download, can all be found in the associated logs.</p><p>Details on each of the files generated by the build process can be found in the file associated with this directory (<a href="https://zenodo.org/records/10065431/files/PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx?download=1">PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx</a>).</p><p> </p><p>🚨 <strong>AVAILABLE FILES </strong>🚨 </p><ul><li>Available KG benchmark files are zipped and listed below.</li><li>For additional details on what each file contains, please see the associated Wiki page 👉 <a href="https://github.com/callahantiff/PheKnowLator/wiki/February-11%2C-2021">here</a>.</li></ul>
PheKnowLator Human Disease KG Benchmarks: Instance-Standard Relations-OWL (v2.0.0 - January 2021)
<p><strong>PKT Human Disease Knowledge Graph Benchmark Builds (v2.0.0)</strong></p><p><strong>Build Type: </strong><i>Instance-Standard Relations-OWL</i></p><p><strong>Build Date: </strong>January 25, 2021</p><p> </p><h3><strong>Important Build Information</strong></h3><p>The benchmarks were originally built and stored using Google Cloud Platform (GCP) resources. For details and a complete description of this process, can be found on GitHub (<a href="https://github.com/callahantiff/PheKnowLator/tree/master/builds#readme">here</a>). Note that we have developed an archive for the builds on Zenodo. While the original GCP resources contained all associated files, due to the file size upload limits associated with each archive, we have limited the uploaded files to the KGs, associated metadata, and log files. The list of resources, including their URLs, and date of download, can all be found in the associated logs.</p><p>Details on each of the files generated by the build process can be found in the file associated with this directory (<a href="https://zenodo.org/records/10065431/files/PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx?download=1">PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx</a>).</p><p> </p><p>🚨 <strong>AVAILABLE FILES </strong>🚨 </p><ul><li>Available KG benchmark files are zipped and listed below.</li><li>For additional details on what each file contains, please see the associated Wiki page 👉 <a href="https://github.com/callahantiff/PheKnowLator/wiki/January-25%2C-2021">here</a>.</li></ul>
PheKnowLator Human Disease KG Benchmarks: Class-Standard Relations-OWLNETS (v2.0.0 - February 2021)
<p><strong>PKT Human Disease Knowledge Graph Benchmark Builds (v2.0.0)</strong></p><p><strong>Build Type: </strong><i>Class-Standard Relations-OWLNETS</i></p><p><strong>Build Date: </strong>February 11, 2021</p><p> </p><h3><strong>Important Build Information</strong></h3><p>The benchmarks were originally built and stored using Google Cloud Platform (GCP) resources. For details and a complete description of this process, can be found on GitHub (<a href="https://github.com/callahantiff/PheKnowLator/tree/master/builds#readme">here</a>). Note that we have developed an archive for the builds on Zenodo. While the original GCP resources contained all associated files, due to the file size upload limits associated with each archive, we have limited the uploaded files to the KGs, associated metadata, and log files. The list of resources, including their URLs, and date of download, can all be found in the associated logs.</p><p>Details on each of the files generated by the build process can be found in the file associated with this directory (<a href="https://zenodo.org/records/10065431/files/PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx?download=1">PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx</a>).</p><p> </p><p>🚨 <strong>AVAILABLE FILES </strong>🚨 </p><ul><li>Available KG benchmark files are zipped and listed below.</li><li>For additional details on what each file contains, please see the associated Wiki page 👉 <a href="https://github.com/callahantiff/PheKnowLator/wiki/February-11%2C-2021">here</a>.</li></ul>
PheKnowLator Human Disease KG Benchmarks: Instance-Inverse Relations-OWL (v2.0.0 - February 2021)
<p><strong>PKT Human Disease Knowledge Graph Benchmark Builds (v2.0.0)</strong></p><p><strong>Build Type: </strong><i>Instance-Inverse Relations-OWL</i></p><p><strong>Build Date: </strong>February 11, 2021</p><p> </p><h3><strong>Important Build Information</strong></h3><p>The benchmarks were originally built and stored using Google Cloud Platform (GCP) resources. For details and a complete description of this process, can be found on GitHub (<a href="https://github.com/callahantiff/PheKnowLator/tree/master/builds#readme">here</a>). Note that we have developed an archive for the builds on Zenodo. While the original GCP resources contained all associated files, due to the file size upload limits associated with each archive, we have limited the uploaded files to the KGs, associated metadata, and log files. The list of resources, including their URLs, and date of download, can all be found in the associated logs.</p><p>Details on each of the files generated by the build process can be found in the file associated with this directory (<a href="https://zenodo.org/records/10065431/files/PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx?download=1">PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx</a>).</p><p> </p><p>🚨 <strong>AVAILABLE FILES </strong>🚨 </p><ul><li>Available KG benchmark files are zipped and listed below.</li><li>For additional details on what each file contains, please see the associated Wiki page 👉 <a href="https://github.com/callahantiff/PheKnowLator/wiki/February-11%2C-2021">here</a>.</li></ul>
PheKnowLator Human Disease KG Benchmarks: Class-Inverse Relations-OWL (v2.0.0 - February 2021)
<p><strong>PKT Human Disease Knowledge Graph Benchmark Builds (v2.0.0)</strong></p><p><strong>Build Type: </strong><i>Class-Inverse Relations-OWL</i></p><p><strong>Build Date: </strong>February 11, 2021</p><p> </p><h3><strong>Important Build Information</strong></h3><p>The benchmarks were originally built and stored using Google Cloud Platform (GCP) resources. For details and a complete description of this process, can be found on GitHub (<a href="https://github.com/callahantiff/PheKnowLator/tree/master/builds#readme">here</a>). Note that we have developed an archive for the builds on Zenodo. While the original GCP resources contained all associated files, due to the file size upload limits associated with each archive, we have limited the uploaded files to the KGs, associated metadata, and log files. The list of resources, including their URLs, and date of download, can all be found in the associated logs.</p><p>Details on each of the files generated by the build process can be found in the file associated with this directory (<a href="https://zenodo.org/records/10065431/files/PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx?download=1">PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx</a>).</p><p> </p><p>🚨 <strong>AVAILABLE FILES </strong>🚨 </p><ul><li>Available KG benchmark files are zipped and listed below.</li><li>For additional details on what each file contains, please see the associated Wiki page 👉 <a href="https://github.com/callahantiff/PheKnowLator/wiki/February-11%2C-2021">here</a>.</li></ul>
PheKnowLator Human Disease KG Benchmarks: Class-Standard Relations-OWL (v2.0.0 - February 2021)
<p><strong>PKT Human Disease Knowledge Graph Benchmark Builds (v2.0.0)</strong></p><p><strong>Build Type: </strong><i>Class-Standard Relations-OWL</i></p><p><strong>Build Date: </strong>February 11, 2021</p><p> </p><h3><strong>Important Build Information</strong></h3><p>The benchmarks were originally built and stored using Google Cloud Platform (GCP) resources. For details and a complete description of this process, can be found on GitHub (<a href="https://github.com/callahantiff/PheKnowLator/tree/master/builds#readme">here</a>). Note that we have developed an archive for the builds on Zenodo. While the original GCP resources contained all associated files, due to the file size upload limits associated with each archive, we have limited the uploaded files to the KGs, associated metadata, and log files. The list of resources, including their URLs, and date of download, can all be found in the associated logs.</p><p>Details on each of the files generated by the build process can be found in the file associated with this directory (<a href="https://zenodo.org/records/10065431/files/PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx?download=1">PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx</a>).</p><p> </p><p>🚨 <strong>AVAILABLE FILES </strong>🚨 </p><ul><li>Available KG benchmark files are zipped and listed below.</li><li>For additional details on what each file contains, please see the associated Wiki page 👉 <a href="https://github.com/callahantiff/PheKnowLator/wiki/February-11%2C-2021">here</a>.</li></ul>
PheKnowLator Human Disease KG Benchmarks: Class-Inverse Relations-OWLNETS (v2.0.0 - February 2021)
<p><strong>PKT Human Disease Knowledge Graph Benchmark Builds (v2.0.0)</strong></p><p><strong>Build Type: </strong><i>Class-InverseRelations-OWLNETS</i></p><p><strong>Build Date: </strong>February 11, 2021</p><p> </p><h3><strong>Important Build Information</strong></h3><p>The benchmarks were originally built and stored using Google Cloud Platform (GCP) resources. For details and a complete description of this process, can be found on GitHub (<a href="https://github.com/callahantiff/PheKnowLator/tree/master/builds#readme">here</a>). Note that we have developed an archive for the builds on Zenodo. While the original GCP resources contained all associated files, due to the file size upload limits associated with each archive, we have limited the uploaded files to the KGs, associated metadata, and log files. The list of resources, including their URLs, and date of download, can all be found in the associated logs.</p><p>Details on each of the files generated by the build process can be found in the file associated with this directory (<a href="https://zenodo.org/records/10065431/files/PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx?download=1">PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx</a>).</p><p> </p><p>🚨 <strong>AVAILABLE FILES </strong>🚨 </p><ul><li>Available KG benchmark files are zipped and listed below.</li><li>For additional details on what each file contains, please see the associated Wiki page 👉 <a href="https://github.com/callahantiff/PheKnowLator/wiki/February-11%2C-2021">here</a>.</li></ul>
LeanDojo Benchmark
<p>Dataset in the paper:</p> <p><a href="https://leandojo.org/">LeanDojo: Theorem Proving with Retrieval-Augmented Language Models</a><br> <a href="https://yangky11.github.io/">Kaiyu Yang</a>, <a href="https://aidanswope.com/about">Aidan Swope</a>, <a href="https://minimario.github.io/">Alex Gu</a>, <a href="https://www.linkedin.com/in/rchalamala">Rahul Chalamala</a>, <a href="https://www.linkedin.com/in/peiyang-song-3279b3251/">Peiyang Song</a>, <a href="https://billysx.github.io/">Shixing Yu</a>, <a href="https://www.linkedin.com/in/saad-godil-9728353/">Saad Godil</a>, <a href="https://www.linkedin.com/in/ryan-prenger-18797ba1/">Ryan Prenger</a>, <a href="http://tensorlab.cms.caltech.edu/users/anima/">Anima Anandkumar</a></p>
Benchmarks for POPL'24 Paper "Commutativity Simplifies Proofs of Parameterized Programs"
<p>This archive contains the benchmark programs used in the POPL'24 paper <i>"Commutativity Simplifies Proofs of Parameterized Programs"</i> by A. Farzan, D. Klumpp and A. Podelski. <a href="https://doi.org/10.1145/3632925">https://doi.org/10.1145/3632925</a></p><p>A preprint of the paper can be found at <a href="https://arxiv.org/abs/2311.02673">https://arxiv.org/abs/2311.02673</a>.</p>
SPIDER - Lumbar spine segmentation in MR images: a dataset and a public benchmark
<p>This is a large publicly available multi-center lumbar spine magnetic resonance imaging (MRI) dataset with reference segmentations of vertebrae, intervertebral discs (IVDs), and spinal canal. The dataset includes 447 sagittal T1 and T2 MRI series from 218 studies of 218 patients with a history of low back pain. The data was collected from four different hospitals. There is an additional hidden test set, not available here, used in the accompanying SPIDER challenge on spider.grand-challenge.org. We share this data to encourage wider participation and collaboration in the field of spine segmentation, and ultimately improve the diagnostic value of lumbar spine MRI.</p> <p>Which MRI studies are assigned to the training and validation sets can be found in the overview file. This file also provides the biological sex for all patients and the age for the patients for which this was available. It also includes a number of scanner and acquisition parameters for each individual MRI study. The dataset also comes with radiological gradings found in a separate file for the following degenerative changes:</p> <p>1.    Modic changes (type I, II or III)</p> <p>2.    Upper and lower endplate changes / Schmorl nodes (binary)</p> <p>3.    Spondylolisthesis (binary)</p> <p>4.    Disc herniation (binary)</p> <p>5.    Disc narrowing (binary)</p> <p>6.    Disc bulging (binary)</p> <p>7.    Pfirrman grade (grade 1 to 5). </p> <p>All radiological gradings are provided per IVD level.</p> <div>This dataset, and the associated public benchmark, are described in this paper: <a href="https://www.nature.com/articles/s41597-024-03090-w" target="_blank" rel="noopener">https://www.nature.com/articles/s41597-024-03090-w</a></div> <div>The public segmenation challenge can be found here: <a href="https://spider.grand-challenge.org/" target="_blank" rel="noopener">https://spider.grand-challenge.org/</a></div> <div> </div> <div>When using this dataset, please cite this dataset with the correct DOI, and also cite the afformentioned paper.</div>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.