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Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder

IEEE Transactions on Pattern Analysis and Machine Intelligence(2022)10.1109/tpami.2022.3185773Source: DataRank Database

Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder is a research paper published in IEEE Transactions on Pattern Analysis and Machine Intelligence (2022). On theSindex it has a DataRank of 0. It has been cited 94 times.

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Open Access94 citations

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Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder · arXiv

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (37 grants)Impact (FWCI 6.10)OA: greenTopics (24)Linked Datasets (1)DataCite Reuse (1)IDs (PubMed, OpenAlex)

FAIR Checklist

Context only (not used in score)

Findable (2/2)

Has DOI
Indexed in repositories

Accessible (1/2)

Open Access

Interoperable (2/2)

DataCite relations
Linked datasets

Reusable (0/3)

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Authors (4)

Elina Thibeau–Sutre ORCID,Ninon Burgos ORCID,Stéphanie Allassonnière ORCID,Clément Chadebec ORCID

Live enrichment

PubMed:35749321 OpenAlex:https://openalex.org/W3157152805

French Government under the management of Agence Nationale de la Recherche

Grant: ANR-19-P3IA-0001

National Institutes of Health

Grant: U01 AG024904

U.S. Department of Defense

Grant: W81XWH-12-2-0012

HPC resources of IDRIS

Grant: 101637

Canadian Institutes of Health Research

Grant: unidentified

unidentified

National Institutes of Health

Grant: 1U01AG024904-01

Alzheimers Disease Neuroimaging Initiative

Araclon Biotech

Cogstate

National Institute of Biomedical Imaging and Bioengineering

Fujirebio

Johnson and Johnson Pharmaceutical Research and Development LLC.

National Institute on Aging

Takeda Pharmaceutical Company

Biogen

Alzheimer's Drug Discovery Foundation

Eisai Inc.

EuroImmun

Janssen Alzheimer Immunotherapy Research and Development, LLC.

Merck and Co., Inc.

Neurotrack Technologies

Novartis Pharmaceuticals Corporation

Roche

CereSpir, Inc.

Pfizer

AbbVie, Alzheimer's Association

Bristol-Myers Squibb Company

GE Healthcare

Grand Equipement National de Calcul Intensif

Transition Therapeutics

Elan Pharmaceuticals, Inc.

IXICO

NeuroRx Research

Piramal Imaging

BioClinica

Eli Lilly and Company

H. Lundbeck A/S

Meso Scale Diagnostics, LLC.

FWCI

6.10

Citation Percentile

1.0%

Citation Trend

2021

2022

2023

2024

2025

2026

greenLicense: IEEE Copyright

repositoryhttps://arxiv.org/pdf/2105.00026

publisherhttp://xplorestaging.ieee.org/ielx7/34/10036240/09806307.pdf?arnumber=9806307

repositoryhttp://arxiv.org/abs/2105.00026

journalhttps://doi.org/10.1109/tpami.2022.3185773

Fields of Study

Generative Adversarial Networks and Image SynthesisAI in cancer detectionDomain Adaptation and Few-Shot Learning0202 electrical engineering, electronic engineering, information engineering02 engineering and technology

Keywords

AutoencoderArtificial intelligencePattern recognition (psychology)Robustness (evolution)Computer scienceConvolutional neural networkClassifier (UML)Metric (unit)Artificial neural networkMachine learningVariational AutoencoderFOS: Computer and information sciencesComputer Science - Machine LearningLatent space representationStatistics - Machine LearningMachine Learning (stat.ML)Data Augmentation[STAT.ML] Statistics [stat]/Machine Learning [stat.ML]Machine Learning (cs.LG)

Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder

10.48550/arxiv.2105.00026arXiv