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On the Reliability of Likelihoods From Conditional Flow Matching Generative Models Trained in Feature Space

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Published in:IET Computer Vision
Format: Online Article RSS Article
Published: 2026
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container_title IET Computer Vision
description
discipline_display Technology & Engineering
discipline_facet Technology & Engineering
format Online Article
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genre Journal Article
id rss_article:26072
institution FRELIP
journal_source_facet IET Computer Vision
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle On the Reliability of Likelihoods From Conditional Flow Matching Generative Models Trained in Feature Space
Image and Video Processing
Technology & Engineering — Computing
Technology & Engineering
sub_discipline_display Technology & Engineering — Computing
sub_discipline_facet Technology & Engineering — Computing
subject_display Image and Video Processing
Technology & Engineering — Computing
Technology & Engineering
Image and Video Processing
Technology & Engineering — Computing
Technology & Engineering
subject_facet Image and Video Processing
Technology & Engineering — Computing
Technology & Engineering
title On the Reliability of Likelihoods From Conditional Flow Matching Generative Models Trained in Feature Space
title_auth On the Reliability of Likelihoods From Conditional Flow Matching Generative Models Trained in Feature Space
title_full On the Reliability of Likelihoods From Conditional Flow Matching Generative Models Trained in Feature Space
title_fullStr On the Reliability of Likelihoods From Conditional Flow Matching Generative Models Trained in Feature Space
title_full_unstemmed On the Reliability of Likelihoods From Conditional Flow Matching Generative Models Trained in Feature Space
title_short On the Reliability of Likelihoods From Conditional Flow Matching Generative Models Trained in Feature Space
title_sort on the reliability of likelihoods from conditional flow matching generative models trained in feature space
topic Image and Video Processing
Technology & Engineering — Computing
Technology & Engineering
url https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/cvi2.70061?af=R