Evidence map›Paper›PMID 37645242›Full record

ArticleJournal of machine learning research : JMLR2022

The Importance of Being Correlated: Implications of Dependence in Joint Spectral Inference across Multiple Networks.

Konstantinos Pantazis, Avanti Athreya, Jesús Arroyo, William N Frost, Evan S Hill, Vince Lyzinski

Open access · greenAbstract read
PubMed Full text at PMC
In one paragraph

Article in Journal of machine learning research : JMLR, 2022. 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, 4 citations in OpenAlex.

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

6 authors at 3 institutions in 1 country.

Konstantinos PantazisDepartment of Mathematics, University of Maryland, College Park, MD 20742.
Avanti AthreyaDepartment of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD 21218.
Jesús ArroyoDepartment of Statistics, Texas A&M University, College Station, TX 77843.
William N FrostCell Biology and Anatomy, and Center for Brain Function and Repair, Chicago Medical School, Rosalind Franklin University of Medicine and Science, Chicago, IL 60064-3905.
Evan S HillCell Biology and Anatomy, and Center for Brain Function and Repair, Chicago Medical School, Rosalind Franklin University of Medicine and Science, Chicago, IL 60064-3905.
Vince LyzinskiDepartment of Mathematics, University of Maryland, College Park, MD 20742.
University of Maryland, College Park · USJohns Hopkins University · USTexas A&M University · US

Funding

A 5-dimensional connectomics approach to the neural basis of behaviorU01NS108637 · NINDS · UNIVERSITY OF MASSACHUSETTS AMHERST · PI KATZ, PAUL S · 2018 to 2020
$3.4M
NeurodevelopmentU01NS123972 · NINDS · UNIVERSITY OF MASSACHUSETTS AMHERST · PI PASCUCCI, VALERIO · 2021 to 2021
$1.0M
NINDS NIH HHS U01 NS108637NINDS NIH HHS U01 NS123972
6 · The paper itself

Abstract

Spectral inference on multiple networks is a rapidly-developing subfield of graph statistics. Recent work has demonstrated that joint, or simultaneous, spectral embedding of multiple independent networks can deliver more accurate estimation than individual spectral decompositions of those same networks. Such inference procedures typically rely heavily on independence assumptions across the multiple network realizations, and even in this case, little attention has been paid to the induced network correlation that can be a consequence of such joint embeddings. In this paper, we present a

Indexed as

induced correlationJoint graph embeddingslatent space network models

Identifiers

PMID37645242
PMCPMC10465120
OpenAlexW3046824338

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.