cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14911327
title: Sample Dataset and Trained Model Parameters for Back-Projection Diffusion

description:  






We have uploaded a sample dataset for training and testing Back-Projection Diffusion. Trained model parameters for the dataset are also provided in tmp.zip.

For a formal description of the dataset, please refer to our paper:

Zhang, B., Guerra, M., Li, Q., & Zepeda-Núñez, L. (2025). Back-Projection Diffusion: Solving the wideband inverse scattering problem with diffusion models. Computer Methods in Applied Mechanics and Engineering, 443, 118036. https://doi.org/10.1016/j.cma.2025.118036

In 10hsquares_trainingdata and 10hsquares_testdata, perturbations are stored as eta.h5 with the following structure:

eta.h5/      ├── /eta

The scattering data are stored as scatter.h5, or as scatter_order_n.h5 (n indicates the order of the stencil used for data generation) with the following structure:

scatter.h5/      ├── /scatter_imag_freq_1      ├── /scatter_real_freq_1      ├── /scatter_imag_freq_2      ├── /scatter_real_freq_2      ├── /scatter_imag_freq_3      ├── /scatter_real_freq_3

The tmp folder contains the trained model parameters.

For usage instructions, please refer to our GitHub repository:

https://github.com/borongzhang/back_projection_diffusion

If this dataset is useful to your research, please cite our paper:@article{ZHANG2025118036,title = {Back-Projection Diffusion: Solving the wideband inverse scattering problem with diffusion models},journal = {Computer Methods in Applied Mechanics and Engineering},volume = {443},pages = {118036},year = {2025},issn = {0045-7825},doi = {https://doi.org/10.1016/j.cma.2025.118036},url = {https://www.sciencedirect.com/science/article/pii/S0045782525003081},author = {Borong Zhang and Martin Guerra and Qin Li and Leonardo Zepeda-Núñez},keywords = {Machine learning, Inverse scattering, Generative modeling, Wave propagation, Diffusion models}}
DOI: 10.15468/dl.uykptb
title: Occurrence Download

description: A dataset containing 63424 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Lomatium Raf."
 ]
}

 The dataset includes 63424 records from 186 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005675-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8y6tfv
title: Occurrence Download

description: A dataset containing 931 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Amara apricaria (Paykull, 1790)",
 "Year is greater than or equal to 1950",
 {
 "or" : [
 "GadmGid is USA",
 "GadmGid is CAN",
 "GadmGid is MEX"
 ]
 }
 ]
}

 The dataset includes 931 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005684-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14760122
title: MRI Brain Perturbations

description: We have uploaded MRI brain perturbations for data generation in Back-Projection Diffusion.  

The Brain MRI images used as our perturbations were obtained from the NYU fastMRI Initiative database (fastmri.med.nyu.edu), as described in the works of Florian Knoll et al., fastmri: A publicly available raw k-space and dicom dataset of knee images for accelerated mr image reconstruction using machine learning, 2020, and Jure Zbontar et al., fastmri: An open dataset and benchmarks for accelerated mri, 2019. As such, NYU fastMRI investigators provided the data but did not participate in the analysis or writing of this report. A listing of NYU fastMRI investigators, subject to updates, can be found at fastmri.med.nyu.edu. The primary goal of fastMRI is to test whether machine learning can aid in the reconstruction of medical images.

We padded, resized, and normalized the perturbations to a native resolution of 240 points. Then, we downsampled the perturbations to resolutions of 60, 80, 120, and 160.

We make the MRI brain perturbations publicly available. They are stored as HDF5 files with filenames in the format eta-n.h5, where n corresponds to the resolution. The files have the following structure:

eta-n.h5/      ├── /eta

For a formal description of the dataset, please refer to our preprint:

Zhang, B., Guerra, M., Li, Q., & Zepeda-Núñez, L. (2025). Back-Projection Diffusion: Solving the wideband inverse scattering problem with diffusion models. Computer Methods in Applied Mechanics and Engineering, 443, 118036. https://doi.org/10.1016/j.cma.2025.118036

For usage instructions for Back-Projection Diffusion, please refer to our GitHub repository.

If this dataset is useful to your research, please cite our preprint:@article{ZHANG2025118036,title = {Back-Projection Diffusion: Solving the wideband inverse scattering problem with diffusion models},journal = {Computer Methods in Applied Mechanics and Engineering},volume = {443},pages = {118036},year = {2025},issn = {0045-7825},doi = {https://doi.org/10.1016/j.cma.2025.118036},url = {https://www.sciencedirect.com/science/article/pii/S0045782525003081},author = {Borong Zhang and Martin Guerra and Qin Li and Leonardo Zepeda-Núñez},keywords = {Machine learning, Inverse scattering, Generative modeling, Wave propagation, Diffusion models}}
DOI: 10.5281/zenodo.14760123
title: MRI Brain Perturbations

description: We have uploaded MRI brain perturbations for data generation in Back-Projection Diffusion.  

The Brain MRI images used as our perturbations were obtained from the NYU fastMRI Initiative database (fastmri.med.nyu.edu), as described in the works of Florian Knoll et al., fastmri: A publicly available raw k-space and dicom dataset of knee images for accelerated mr image reconstruction using machine learning, 2020, and Jure Zbontar et al., fastmri: An open dataset and benchmarks for accelerated mri, 2019. As such, NYU fastMRI investigators provided the data but did not participate in the analysis or writing of this report. A listing of NYU fastMRI investigators, subject to updates, can be found at fastmri.med.nyu.edu. The primary goal of fastMRI is to test whether machine learning can aid in the reconstruction of medical images.

We padded, resized, and normalized the perturbations to a native resolution of 240 points. Then, we downsampled the perturbations to resolutions of 60, 80, 120, and 160.

We make the MRI brain perturbations publicly available. They are stored as HDF5 files with filenames in the format eta-n.h5, where n corresponds to the resolution. The files have the following structure:

eta-n.h5/      ├── /eta

For a formal description of the dataset, please refer to our preprint:

Zhang, B., Guerra, M., Li, Q., & Zepeda-Núñez, L. (2025). Back-Projection Diffusion: Solving the wideband inverse scattering problem with diffusion models. Computer Methods in Applied Mechanics and Engineering, 443, 118036. https://doi.org/10.1016/j.cma.2025.118036

For usage instructions for Back-Projection Diffusion, please refer to our GitHub repository.

If this dataset is useful to your research, please cite our preprint:@article{ZHANG2025118036,title = {Back-Projection Diffusion: Solving the wideband inverse scattering problem with diffusion models},journal = {Computer Methods in Applied Mechanics and Engineering},volume = {443},pages = {118036},year = {2025},issn = {0045-7825},doi = {https://doi.org/10.1016/j.cma.2025.118036},url = {https://www.sciencedirect.com/science/article/pii/S0045782525003081},author = {Borong Zhang and Martin Guerra and Qin Li and Leonardo Zepeda-Núñez},keywords = {Machine learning, Inverse scattering, Generative modeling, Wave propagation, Diffusion models}}
DOI: 10.15468/dl.ccb8xu
title: Occurrence Download

description: A dataset containing 169 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Diplocheila obtusa (LeConte, 1847)",
 "Year is greater than or equal to 1950",
 {
 "or" : [
 "GadmGid is USA",
 "GadmGid is CAN",
 "GadmGid is MEX"
 ]
 }
 ]
}

 The dataset includes 169 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005688-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sxeuyf
title: Occurrence Download

description: A dataset containing 106 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Lomatocarpa Pimenov"
 ]
}

 The dataset includes 106 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005686-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ng95m5
title: Occurrence Download

description: A dataset containing 743 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Arceuthobium vaginatum subsp. cryptopodum (Engelm.) Hawksw. & Wiens"
 ]
}

 The dataset includes 743 records from 40 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005687-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wsqydw
title: Occurrence Download

description: A dataset containing 2808 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Amara quenseli (Schönherr, 1806)",
 "Year is greater than or equal to 1950",
 {
 "or" : [
 "GadmGid is USA",
 "GadmGid is CAN",
 "GadmGid is MEX"
 ]
 }
 ]
}

 The dataset includes 2808 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005690-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.539h6s
title: Occurrence Download

description: A dataset containing 4196 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Lomatogonium A.Braun"
 ]
}

 The dataset includes 4196 records from 130 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005691-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6uza2b
title: Occurrence Download

description: A dataset containing 2633053 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Aves",
 "HasCoordinate is true",
 "BasisOfRecord is Human Observation",
 "Year is greater than or equal to 2010",
 "Year is less than or equal to 2010",
 "Month is March",
 "Day is greater than or equal to 1",
 "Day is less than or equal to 31"
 ]
}

 The dataset includes 2633053 records from 430 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000523-250424135625364/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/12004800
title: World Weather Repository ( Daily Updating )
DOI: 10.15468/dl.c46vsy
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((103.772 -2.087,104.289 -2.087,104.289 -1.646,103.772 -1.646,103.772 -2.087))",
 "OccurrenceStatus is Present",
 "TaxonKey is Squamata"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008349-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cj6guf
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Allotropa burrelli"
 ]
}

 The dataset includes 12 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038815-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9mprjh
title: Occurrence Download

description: A dataset containing 1080 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Boreus westwoodi Hagen, 1866"
 ]
}

 The dataset includes 1080 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0102219-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nybfh2
title: Occurrence Download

description: A dataset containing 7553 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Crucianella maritima L."
 ]
}

 The dataset includes 7553 records from 204 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0102213-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4zvwq4
title: Occurrence Download

description: A dataset containing 7028 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Eucera longicornis",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Observation, Occurrence evidence)",
 "OccurrenceStatus is Present",
 "HasCoordinate is true"
 ]
}

 The dataset includes 7028 records from 137 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038817-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/7pwum9
title: Woody plants occurrence across Namibia, 2023

description: This dataset comprises woody plant occurrence records collected across eight regions of Namibia: Kunene, Karas, Khomas, Kavango East, Oshana, Oshikoto, Zambezi, and Hardap, during the November to December 2023 field campaign. The purpose of the study was to assess the structure, composition, and diversity of woody vegetation communities along environmental gradients, providing baseline data for long-term vegetation monitoring, ecological modeling, and conservation planning across Namibia.
Woody plant surveys were systematically conducted within standardized 50 × 50-meter plots established at each sampling site. Within each plot, all woody plants that are 1.3m or above were assessed.
For each qualifying individual, the following parameters were documented:
Scientific species name, supplemented by vernacular (local or english) names where available,
DBH measuring tape,
Height, measured using the MeasureHeights mobile application,
Canopy structure, described using two standardized categories, Canopy 1 and Canopy 2, which refer to the vertical and horizontal complexity of the canopy.
Species identification was performed in the field using a combination of regional botanical field guides and the iNaturalist mobile application, ensuring accurate and consistent taxonomic resolution. For each plot, GPS coordinates of the central point were recorded using a Garmin handheld GPS unit, ensuring precise geolocation of observations.
A rapid sampling was also done in different plots, were trees were not measured but rather given a category. Tree abundance within the designated plot was quantified using a categorical scale ranging from 1 to 5, where a rating of 1 denoted the least prevalent species, and a rating of 5 indicated the species with the highest dominance. The rapid sampling was done to increase the spatial coverage within the time period of sampling and also to establish if eDNA metabarcoding will pick up what direct observation picked up.
The dataset is taxonomically rich and reflects the floristic composition typical of Namibia’s savannas, dry woodlands, and arid shrubland. Some of the families recorded are: Euphorbiaceae, Burseraceae, Rhamnaceae, Capparaceae, Loganiaceae, Myrtales, Sapindales, Lamiales and Ochnaceae. 
This dataset provides high-resolution floristic and structural information on woody vegetation across Namibia’s key ecological zones. It is especially valuable for assessing the impacts of environmental gradients, land use, and climate variability on woody plant communities. Additionally, the data form an essential foundation for future studies incorporating plant trait analysis, carbon stock estimation, and vegetation classification using remote sensing.
DOI: 10.15468/dl.pgv5jz
title: Occurrence Download

description: A dataset containing 30 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Abelia mexicana"
 ]
}

 The dataset includes 30 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038818-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/ar/nvurhc
title: BS Sallandsweg 14, Diepenveen

description: Dit document is opgesteld in het kader van de aanleg van een nieuw zwembad aan de Sallandsweg 14. Op de vigerende archeologische beleidskaart, vastgesteld in 2015, kent het plangebied archeologische beleidswaarde 3 en voornamelijk beleidswaarde 5. Deze beleidswaarden zijn in het tijdelijke omgevingsplan (voorheen Chw bestemmingsplan Buitengebied Deventer, 1e herziening) vertaald naar de regels (voorheen dubbelbestemming) ‘Waarde – Archeologie – 3’ en ‘Waarde – Archeologie – 5’. Bij de voorgenomen plannen kan gesteld worden dat er in ieder geval meer dan 40 m2, dieper dan 30 cm, wordt verstoord en dat daarmee 
de vrijstellingsgrens en de onderzoeksgrens van beleidswaarde 5 worden overschreden (respectievelijk 10 m2 en 40 m2).
DOI: 10.15468/dl.ahvmkf
title: Occurrence Download

description: A dataset containing 120158 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is VectorNet observations"
 ]
}

 The dataset includes 120158 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038809-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hjmxtv
title: Occurrence Download

description: A dataset containing 55 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (China, Chinese Taipei, Hong Kong, Macao)",
 "TaxonKey is Oreomecon nudicaulis"
 ]
}

 The dataset includes 55 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038819-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p2y33n
title: Occurrence Download

description: A dataset containing 523 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Eucera oraniensis",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Observation, Occurrence evidence)",
 "OccurrenceStatus is Present",
 "HasCoordinate is true"
 ]
}

 The dataset includes 523 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038820-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uvbkuw
title: Occurrence Download

description: A dataset containing 1971 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Abelia serrata"
 ]
}

 The dataset includes 1971 records from 86 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038824-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.etvqy3
title: Occurrence Download

description: A dataset containing 2389 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lepus saxatilis"
 ]
}

 The dataset includes 2389 records from 55 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038825-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/ar/pmwozy
title: BS Hanzeweg 19, Deventer

description: Dit document is opgesteld in het kader van de ontwikkeling van het plangebied, waarbij grootschalige nieuwbouw zal plaatsvinden. Het plangebied is gelegen in een dynamisch landschap waarbij water in de vorm van doorbraken grote invloed kan hebben gehad op het bodemarchief. Geomorfologisch gezien is er een duincomplex in het plangebied aanwezig waardoor theoretisch gezien een hoge archeologische verwachting geldt voor resten uit de prehistorie en Romeinse tijd. Het is echter de vraag in hoeverre hiervan nog resten aanwezig zijn en of het gebied niet verspoeld is geraakt door de verschillende overstromingen. Een verkennend booronderzoek kan hier uitsluitsel geven.
DOI: 10.15468/dl.846s4f
title: Occurrence Download

description: A dataset containing 9524 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Phylogenomics and the rise of the angiosperms"
 ]
}

 The dataset includes 9524 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038822-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/caqqds
title: Suivi des oiseaux de passage : programme ACT - Programme ACT : Répartition Grive littorne 2012 - 2016 Coordonnées GPS Lambert 93

description: Aire de reproduction de l'espèce Grive littorne fondée sur la présence de mâles chanteurs au printemps (avril – juin), à partir de points d’écoutes répartis le long d’itinéraires échantillons. Environ 5 000 points ont été visités chaque année entre 2012 et 2016
DOI: 10.34740/kaggle/dsv/13649835
title: Blood Donation Portal Dataset
DOI: 10.34740/kaggle/dsv/13649627
title: Transportation and Accident Prediction Dataset
DOI: 10.15468/dl.qqvyqs
title: Occurrence Download

description: A dataset containing 90 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is TLS",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Orchidaceae"
 ]
}

 The dataset includes 90 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038827-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.