GEODESIC SINKHORN FOR FAST AND ACCURATE OPTIMAL TRANSPORT ON MANIFOLDS.

Guillaume Huguet, Alexander Tong, María Ramos Zapatero, Christopher J Tape, Guy Wolf, Smita Krishnaswamy

Abstract readPreprint

In one paragraph

Article in ArXiv, 2023. 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

6 authors.

Guillaume HuguetUniversité de Montréal; Mila - Quebec AI Institute.

Alexander TongUniversité de Montréal; Mila - Quebec AI Institute.

María Ramos ZapateroUniversity College London Cancer Institute.

Christopher J TapeUniversity College London Cancer Institute.

Guy WolfUniversité de Montréal; Mila - Quebec AI Institute.

Smita KrishnaswamyYale University.

Funding

Finding emergent structure in multi-sample biological data with the dual geometry of cells and features R01GM135929 · NIGMS · MICHIGAN STATE UNIVERSITY · PI BROWN, EDWARD · 2019 to 2022

$1.4M

NIGMS NIH HHS R01 GM135929

6 · The paper itself

Abstract

Efficient computation of optimal transport distance between distributions is of growing importance in data science. Sinkhorn-based methods are currently the state-of-the-art for such computations, but require

Identifiers

PMID37808090

PMCPMC10557786

What OpenQuestion holds

Textmetadata

LicenceCC BY

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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 OpenQuestion graph.