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Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes

PubMed(2023)10.48550/arxiv.2302.04534Source: DataRank Database

Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes is a research paper published in PubMed (2023). On theSindex it has a DataRank of 0. It has been cited 1 time.

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0DataRank · unranked

Scored on demand from live citation data

Open Access1 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (4 grants)Impact (FWCI 0.13)OA: greenTopics (31)IDs (PubMed, PMC, OpenAlex)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (4)

Babak Shahbaba ORCID,Stephan Mandt ORCID,Maurizio Filippone ORCID,Ba-Hien Tran

Live enrichment

PubMed:38644959 PMC:PMC11031196 OpenAlex:https://openalex.org/W4320342618

NIMH NIH HHS

Grant: R01 MH115697

National Science Foundation

Grant: 2007719

RI: Small: Deep Variational Data Compression

National Science Foundation

Grant: 2003237

MLWiNS: Ultra-Reliable Collaborative Computing for Autonomous Unmanned Aerial Vehicles

French National Research Agency (ANR)

Grant: ANR-19-P3IA-0002

FWCI

0.13

Citation Percentile

0.5%

Citation Trend

2024

greenLicense: cc-by

repositoryhttps://arxiv.org/pdf/2302.04534

repositoryhttp://arxiv.org/abs/2302.04534

repositoryhttps://pubmed.ncbi.nlm.nih.gov/38644959

repositoryhttps://hal.science/hal-04188337

repositoryhttps://escholarship.org/uc/item/47m3r5v9

Fields of Study

Gaussian Processes and Bayesian InferenceGenerative Adversarial Networks and Image SynthesisMachine Learning in Healthcare0202 electrical engineering, electronic engineering, information engineering02 engineering and technology01 natural sciences0105 earth and related environmental sciences

Keywords

AutoencoderPrior probabilityArtificial intelligenceComputer scienceBayesian probabilityGaussian processMachine learningGenerative modelBayesian inferenceLatent variableRepresentation (politics)Posterior probabilityPattern recognition (psychology)GaussianMarkov chain Monte CarloSparse approximationAlgorithmGenerative grammarDeep learningFOS: Computer and information sciencesComputer Science - Machine LearningStatistics - Machine LearningMachine Learning (stat.ML)Machine Learning (cs.LG)