Pilot corpus: NIH-funded biomedical datasets. Any DOI can be scored on demand — network effects sharpen as coverage grows.

Computing With Residue Numbers in High-Dimensional Representation

Neural Computation(2024)10.1162/neco_a_01723Source: DataRank Database

Computing With Residue Numbers in High-Dimensional Representation is a research paper published in Neural Computation (2024). On theSindex it has a DataRank of 0. It has been cited 10 times.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access10 citations

Download PDF

Cite:

DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?

›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (3 grants)Impact (FWCI 1.35)OA: bronzeTopics (28)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)

FAIR checklist signals are shown for context only and do not affect DataRank scoring.

Run a calibrated FAIR evaluation for this paper →

We only score data papers we can read in full — never from an abstract alone.

Authors (7)

Denis Kleyko ORCID,E. Paxon Frady ORCID,Connor Bybee ORCID,Pentti Kanerva ORCID,Friedrich T. Sommer ORCID

Live enrichment

PubMed:39556514 PMC:PMC11647909 OpenAlex:https://openalex.org/W4388870647

NIBIB NIH HHS

Grant: R01 EB026955

National Institutes of Health

Grant: 5R01EB026955-03

Building analysis tools and a theory framework for inferring principles of neural computation from multi-scale organization in brain recordings

European Commission

Grant: 839179

A Low-Power Artificial Intelligence Framework based on Vector Symbolic Architectures

FWCI

1.35

Citation Percentile

0.8%

Citation Trend

2024

2025

2026

bronzeLicense: CC BY SA

journalhttps://direct.mit.edu/neco/article-pdf/37/1/1/2483438/neco_a_01723.pdf

publisherhttps://direct.mit.edu/neco/article-pdf/37/1/1/2483438/neco_a_01723.pdf

journalhttps://doi.org/10.1162/neco_a_01723

repositoryhttps://pubmed.ncbi.nlm.nih.gov/37986727

repositoryhttps://pubmed.ncbi.nlm.nih.gov/39556514

Fields of Study

Ferroelectric and Negative Capacitance DevicesNeural Networks and Reservoir ComputingAdvanced Memory and Neural Computing02 engineering and technology0202 electrical engineering, electronic engineering, information engineering

Keywords

Parallelizable manifoldComputer scienceResidue number systemRobustness (evolution)Theoretical computer scienceAlgebraic operationAlgebraic numberAlgorithmMathematicshyperdimensional computingFOS: Computer and information sciencesOther nonclassical models of computationComputer Science - Machine Learningresidue numberComputer Science - Neural and Evolutionary Computing510004Machine Learning (cs.LG)Quantitative Biology - Neurons and CognitionFOS: Biological sciencesNeurons and Cognition (q-bio.NC)Neural and Evolutionary Computing (cs.NE)high-dimensional representation