Evidence map›Paper›PMID 33088027›Full record

ArticleStatistics and computing2020

Convergence rates of Gaussian ODE filters.

Hans Kersting, T J Sullivan, Philipp Hennig

Abstract read
In one paragraph

Article in Statistics and computing, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Hans KerstingUniversity of Tübingen and Max Planck Institute for Intelligent Systems, Maria-von-Linden-Straße 6, 72076 Tübingen, Germany.ORCID 0000-0002-2782-868X
T J SullivanUniversity of Warwick, Coventry, CV4 7AL United Kingdom.
Philipp HennigUniversity of Tübingen and Max Planck Institute for Intelligent Systems, Maria-von-Linden-Straße 6, 72076 Tübingen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A recently introduced class of probabilistic (uncertainty-aware) solvers for ordinary differential equations (ODEs) applies Gaussian (Kalman) filtering to initial value problems. These methods model the true solution

Indexed as

Gaussian processesInitial value problemsMarkov processesNumerical analysisOrdinary differential equationsProbabilistic numerics

Identifiers

PMID33088027
PMCPMC7527376

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.