Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Schmutz, Hugo"'
Autor:
Sportisse, Aude, Schmutz, Hugo, Humbert, Olivier, Bouveyron, Charles, Mattei, Pierre-Alexandre
Semi-supervised learning is a powerful technique for leveraging unlabeled data to improve machine learning models, but it can be affected by the presence of ``informative'' labels, which occur when some classes are more likely to be labeled than othe
Externí odkaz:
http://arxiv.org/abs/2302.07540
Semi-supervised learning (SSL) provides an effective means of leveraging unlabelled data to improve a model performance. Even though the domain has received a considerable amount of attention in the past years, most methods present the common drawbac
Externí odkaz:
http://arxiv.org/abs/2203.07512
Autor:
Bergamin, Federico, Mattei, Pierre-Alexandre, Havtorn, Jakob D., Senetaire, Hugo, Schmutz, Hugo, Maaløe, Lars, Hauberg, Søren, Frellsen, Jes
We present simple methods for out-of-distribution detection using a trained generative model. These techniques, based on classical statistical tests, are model-agnostic in the sense that they can be applied to any differentiable generative model. The
Externí odkaz:
http://arxiv.org/abs/2203.01097
Autor:
Immunological Genome Project, Maslova, Alexandra, Ramirez, Ricardo N., Ma, Ke, Schmutz, Hugo, Wang, Chendi, Fox, Curtis, Ng, Bernard, Benoist, Christophe, Mostafavi, Sara
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America, 2020 Oct . 117(41), 25655-25666.
Externí odkaz:
https://www.jstor.org/stable/26969640
Autor:
Comte, Victor1 (AUTHOR) vcomte@pm.me, Schmutz, Hugo2 (AUTHOR), Chardin, David1,2 (AUTHOR), Orlhac, Fanny3 (AUTHOR), Darcourt, Jacques1,2 (AUTHOR), Humbert, Olivier1,2 (AUTHOR)
Publikováno v:
European Journal of Nuclear Medicine & Molecular Imaging. Sep2022, Vol. 49 Issue 11, p3787-3796. 10p. 2 Diagrams, 4 Charts, 1 Graph.
Autor:
Sportisse, Aude, Schmutz, Hugo, Humbert, Olivier, Bouveyron, Charles, Mattei, Pierre-Alexandre
Semi-supervised learning is a powerful technique for leveraging unlabeled data to improve machine learning models, but it can be affected by the presence of “informative” labels, which occur when some classes are more likely to be labeled than ot
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::ab823709f14356e2dc0634ec0602f6c5
https://hal.science/hal-03982898
https://hal.science/hal-03982898
Publikováno v:
European Journal of Nuclear Medicine and Molecular Imaging
EANM 2022-35th Annual Congres-Annual Congress of the European Association of Nuclear Medicine
EANM 2022-35th Annual Congres-Annual Congress of the European Association of Nuclear Medicine, Oct 2022, Barcelona, Spain. pp.245, ⟨10.1007/s00259-022-05924-4⟩
EANM 2022-35th Annual Congres-Annual Congress of the European Association of Nuclear Medicine
EANM 2022-35th Annual Congres-Annual Congress of the European Association of Nuclear Medicine, Oct 2022, Barcelona, Spain. pp.245, ⟨10.1007/s00259-022-05924-4⟩
International audience; In patients with non-small cell lung cancer (NSCLC) treated with immunotherapy, individual biological and PET imaging prognostic biomarkers have been recently identified. However, combination of biomarkers has not been studied
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::000442302050cd423c5e87601cb88662
https://hal.science/hal-03876074
https://hal.science/hal-03876074
Semi supervised learning (SSL) provides an effective means of leveraging unlabelled data to improve a model's performance. Even though the domain has received a considerable amount of attention in the past years, most methods present the common drawb
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::6ff15d01be0704350eeff63deb982c6c
https://hal.science/hal-03610272
https://hal.science/hal-03610272
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.