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Mathematical datasets, statistical benchmarks, probability, optimization, operations research
2,464 datasets
UKCCSRC Call 2 project data from a presentation on CO2 Flow Metering through Multi-Modal Sensing and Statistical Data Fusion, presented at the UKCCSRC Edinburgh Biannual Meeting on 15.09.2016. The project, with grant number UKCCSRC-C2-218, was contributed by the British Geological Survey (BGS). The dataset was last updated in the platform on 2026-04-09.
Purdue University researchers developed a four-step disassembly procedure enabling LCD monitor recycling in under 4 minutes. The work addresses the challenge of mercury-containing backlights in hundreds of millions of end-of-life displays. The methodology and tool designs were published by Issst Proc.
Results of a paired Wilcoxon signed-rank test comparing the performance of a baseline model and the SCEAF-UNet architecture for medical image segmentation. The dataset, 5.5 KB in size, was authored by Lingyun Zhao and last updated on March 25, 2026. It is shared under a CC-BY-4.0 license on figshare.
Figshare hosts a summary of mean C:N ratios across habitat contexts, calculated from values in each core section. The dataset, authored by Anne Margaret H. Smiley, includes superscripts indicating statistical significance. Row and column counts are unknown.
A small dataset created by Bharat Srikishan to accompany the paper SPEC: An Evaluation Framework for Stochastic PDE Surrogates. The dataset is hosted on Harvard Dataverse and was last updated on May 6, 2026.
Two supplementary tables from a study on tick-borne infection tolerance in wild sloths. Table S1 contains sloth data, and Table S2 contains statistical models. The dataset was authored by Olivier Duron and last updated on April 22, 2026.
A 5.5 KB Excel file contains statistical results from three analytical methods, authored by Yunqi Liao. The dataset is licensed under CC BY 4.0 and was last updated in March 2026.
Metasens implements six statistical methods for sensitivity analysis in meta-analysis, supporting the work of Schwarzer et al. (2015). The methods include the Copas selection model, limit meta-analysis, and imputation methods for missing binary data. The package is authored by Guido Schwarzer.
RoBMA is a framework for estimating ensembles of meta-analytic, meta-regression, and multilevel models. It uses Bayesian model-averaging to combine competing models, weights posterior parameter distributions based on posterior model probabilities, and uses Bayes factors to test for the presence or absence of components like an effect or heterogeneity. The package, authored by František Bartoš, provides functions for summary, visualizations, and fit diagnostics.
Alpaca is a dataset classified as a male-oriented scientific and mathematical collection created by makhi burroughs. The dataset was uploaded to Hugging Face by the user netcat420. Its last recorded metadata update was on 2026-05-01 10:10:35.
NASA GES DISC provides statistical summaries of VIIRS cloud mask and Level 1B data collocated within CrIS instrument footprints from the NOAA-20 satellite. The Cross-track Infrared Sounder (CrIS) data includes 2,223 spectral channels across shortwave, midwave, and longwave infrared bands. Products are generated on six-minute boundaries from the Joint Polar Satellite System-1 mission.
Monthly statistical mean values of cloud liquid water over ocean areas, derived from the AMSR2 sensor onboard the GCOM-W satellite. The dataset, produced by the Japan Aerospace Exploration Agency (JAXA), provides gridded data at a 0.1-degree resolution. It includes mean values, standard deviations, and counts of valid observations for each grid cell.
AMSR2 sensor data provides monthly mean snow depth over land on a 0.25-degree global grid. The Japan Aerospace Exploration Agency (JAXA) produces this dataset from the GCOM-W satellite launched in 2012. It includes statistical metrics like standard deviation and data counts for each grid cell.
AMSR2 satellite sensor data provides daily global snow depth measurements over land at a 0.1-degree grid resolution. The Japan Aerospace Exploration Agency (JAXA) produces this Level 3 dataset by averaging one day's worth of Level 1B and Level 2 observations. This product enables tracking of global snow cover distribution changes related to climate variation.
Monthly statistical means of integrated water vapor over ocean surfaces, derived from the AMSR2 sensor onboard the GCOM-W satellite. The Japan Aerospace Exploration Agency (JAXA) produces this dataset, which provides data on a 0.25-degree grid. Observations began after the satellite's launch in May 2012.
Global daily and monthly statistical means of vertically integrated cloud liquid water over ocean surfaces, measured in kilograms per square meter. The dataset is derived from Level 1B and Level 2 data collected by the AMSR2 sensor onboard the JAXA GCOM-W satellite, which launched in May 2012. Data is provided on a 0.1-degree grid in HDF5 format, with separate calculations for ascending and descending satellite tracks.
Brightness temperature measurements at 89GHz are derived from the AMSR2 sensor aboard the JAXA GCOM-W satellite. Data represents daily statistical mean values on a 0.1-degree global grid, calculated separately for ascending and descending satellite tracks. The Japan Aerospace Exploration Agency (JAXA) produces this dataset, with observations beginning after the satellite's launch in May 2012.
Global monthly averaged brightness temperature data at 7GHz, derived from the AMSR2 sensor onboard the JAXA GCOM-W satellite. The dataset provides statistical means, standard deviations, and observation counts on a 0.1-degree grid for each month. It is produced by the Japan Aerospace Exploration Agency (JAXA) from observations beginning after the satellite's launch in May 2012.
GCOM-W/AMSR2 L3 Brightness Temperature data provides monthly averaged microwave brightness temperature at 6GHz on a 0.25-degree global grid. The dataset is produced by the Japan Aerospace Exploration Agency (JAXA) from observations by the AMSR2 sensor launched in May 2012. It contains statistical mean values for ascending and descending satellite tracks, along with standard deviation and data count fields.
Brightness temperature measurements at 6GHz from the AMSR2 sensor onboard the JAXA GCOM-W satellite. Data is provided as daily statistical means on a global 0.1-degree grid, with separate values for horizontal and vertical polarizations. The satellite was launched in May 2012, and the dataset is produced by the Japan Aerospace Exploration Agency.