Skip to main content
Powered by ShareScore

Find research datasets worth reusing

Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.

8

datasets available to search

ShareScore release 0.9.0

Reset

Dataset results

8 results for “meta-learning”

Learn how ShareScore rates datasets ↗
zenodo40/100

Delaunay data set learn2learn l2l for meta-learning and few-shot learning

<p>Delaunay data set learn2learn l2l for meta-learning and few-shot learning. We split it into 3 meta-train, meta-val and meta-test sets.&nbsp;</p> <p>&nbsp;</p> <p>For details of original data see:&nbsp;https://github.com/camillegontier/DELAUNAY_dataset</p>

opencc-by-4.0Mar 2023View details →
zenodo36/100

Enabling Reproducibility and Meta-learning Through a Lifelong Database of Experiments (LDE)

<p>Replication dataset for experiments performed in MLSys 2021 submission: &quot;Enabling Reproducibility and Meta-learning Through a Lifelong Database of Experiments (LDE)&quot;</p> <p>(currently using a placeholder to acquire link for submission, will update with dataset)</p>

opencc-by-4.0Oct 2020View details →
zenodo36/100

The raw data from the article "KinomeMETA: meta-learning enhanced kinome-wide polypharmacology profiling"

<p>The raw data from the article "KinomeMETA: meta-learning enhanced kinome-wide polypharmacology profiling"</p>

opencc-by-4.0Nov 2023View details →
zenodo32/100

Meta-learning an Intermediate Representation for Few-shot Block-wise Prediction of Landslide Susceptibility

<p>This upload contains 1) the used thematic maps in the study,&nbsp;2) the samples to train and validate the proposed model, and 3) the samples used to predict landslide susceptibility of Fengjie County and Fuling District. The code related to the methods is available on the website:&nbsp;<a href="https://github.com/Young-Excavator/Meta_LSM">https://github.com/Young-Excavator/Meta_LSM</a>.</p>

opencc-by-4.0Jan 2022View details →
zenodo32/100

LML-Learning Meta-Learning Dataset_update version

<p>The LML dataset presented in this paper contains both categorical and continuous data for 7 meta-learning parameters: age, gender, degree of illusion of competence, sleep duration, chronotype, experience of imposter phenomenon and multiple intelligence. Convenience sampling and simple random sampling method are used to structure the volunteered anonymous online survey data collection project for LML dataset creation. Survey questionnaires are set to explore adult learners&#39; (age over 18) meta-learning parameters. The responses from the 54 survey questionnaires contains raw data from 1021 current university students from 11 universities of Bangladesh.</p> <p>Mean and standard deviation for the participant&#39;s baseline attributes are given for scale parameters, and frequency and percentage are calculated for categorical parameters. Academic curriculum, courses as well as professional training materials can be reviewed and re-designed with focusing on the diversity of learners. How the designed courses will be learned by learners along with how they will be taught is a significant point for education in any discipline. As the survey questionnaires are set for adult learners and only current university students have participated in this survey, this dataset is appropriate for study andragogy and heutagogy but pedagogy.</p> <p>Ethics statements Ethical approval (Involvement of Human Subjects) were obtained from the Biosafety, Biosecurity and Ethical Clearance Committee, Jahangirnagar University (reference no. is BBEC,JU/M 2022/01 (18)). The dataset presented in this article is open for public access. It is mandatory to follow the correct citation guidelines when using this LML dataset.</p> <p>Credit author statement Sonia Corraya: Conceptualization, Methodology, Data curation, Visualization, Writing &ndash; original draft; Professor Shamim Al Mamun: Supervision; Professor M. Shamim Kaiser: Supervision.</p> <p>This dataset belongs to Authors, Institute of Information Technology, Jahangirnagar University, savar, Dhaka-1342, Bangladesh.</p>

opencc-by-4.0Jul 2023View details →
zenodo28/100

Task-Informed Meta-Learning data

<p>Data accompanying the Task-Informed Meta-Learning codebase (https://github.com/nasaharvest/timl).</p>

opencc-by-4.0Feb 2022View details →
zenodo28/100

Few-Shot Meta-Learning Applied to Whole Brain Activity Maps Improves Systems Neuropharmacology and Drug Discovery

<p>Data and Code are all included</p>

opencc-by-4.0Aug 2024View details →
zenodo24/100

Physics-aware Spatiotemporal Modules with Auxiliary Tasks for Meta-Learning

<p>Datasets and pre-trained models for NeurIPS 2020 submission &quot;Physics-aware&nbsp;Spatiotemporal&nbsp;Modules&nbsp;with&nbsp;Auxiliary&nbsp;Tasks&nbsp;for&nbsp;Meta-Learning&quot;.</p>

opencc-by-4.0Jun 2020View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record