Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Marco Cuturi"'
Publikováno v:
NeuroImage, Vol 220, Iss , Pp 116847- (2020)
Magnetoencephalography and electroencephalography (M/EEG) are non-invasive modalities that measure the weak electromagnetic fields generated by neural activity. Estimating the location and magnitude of the current sources that generated these electro
Externí odkaz:
https://doaj.org/article/3e7aab947e0345fbb9f70ba3dde9db50
Publikováno v:
Entropy, Vol 19, Iss 2, p 47 (2017)
Nonparametric two-sample or homogeneity testing is a decision theoretic problem that involves identifying differences between two random variables without making parametric assumptions about their underlying distributions. The literature is old and r
Externí odkaz:
https://doaj.org/article/089cd3d1923c432d83dc31b67447fe11
Autor:
Dominik Klein, Giovanni Palla, Marius Lange, Michal Klein, Zoe Piran, Manuel Gander, Laetitia Meng-Papaxanthos, Michael Sterr, Aimée Bastidas-Ponce, Marta Tarquis-Medina, Heiko Lickert, Mostafa Bakhti, Mor Nitzan, Marco Cuturi, Fabian J. Theis
Single-cell genomics technologies enable multimodal profiling of millions of cells across temporal and spatial dimensions. Experimental limitations prevent the measurement of all-encompassing cellular states in their native temporal dynamics or spati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::50b59ee5c2043e337fec8b03b539ec3a
https://doi.org/10.1101/2023.05.11.540374
https://doi.org/10.1101/2023.05.11.540374
Autor:
Laetitia Meng-Papaxanthos, Ran Zhang, Gang Li, Marco Cuturi, William Stafford Noble, Jean-Philippe Vert
MotivationModality matching in single-cell omics data analysis—i.e., matching cells across data sets collected using different types of genomic assays—has become an important problem, because unifying perspectives across different technologies ho
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::772864181a52a6f92ddb26491fcd9ac3
https://doi.org/10.1101/2022.03.23.485536
https://doi.org/10.1101/2022.03.23.485536
Publikováno v:
SIGGRAPH Asia 2021 Courses.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::09baeabc34506f64241686f07ceed6f6
https://doi.org/10.1145/3476117.3483441
https://doi.org/10.1145/3476117.3483441
Publikováno v:
Neural Computation. 31:827-848
We propose a new divergence on the manifold of probability distributions, building on the entropic regularization of optimal transportation problems. As Cuturi ( 2013 ) showed, regularizing the optimal transport problem with an entropic term is known
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3138b6b243a6b619b7216394d38894f3
https://doi.org/10.1162/neco_a_01178
https://doi.org/10.1162/neco_a_01178
Autor:
Gabriel Peyré, Marco Cuturi
Publikováno v:
SIAM Review
Variational problems that involve Wasserstein distances and more generally optimal transport (OT) theory are playing an increasingly important role in data sciences. Such problems can be used to form an examplar measure out of various probability mea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b602b88b01a3275981ff6313698c40df
https://doi.org/10.1137/18m1208654
https://doi.org/10.1137/18m1208654
Publikováno v:
SIAM Journal on Scientific Computing. 40:B429-B456
This paper is concerned with the statistical analysis of datasets whose elements are random histograms. For the purpose of learning principal modes of variation from such data, we consider the issue of computing the principal component analysis (PCA)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3ebbb1055afb144c701f47a9831e8004
https://doi.org/10.1137/17m1143459
https://doi.org/10.1137/17m1143459
Publikováno v:
Journal of Mathematical Imaging and Vision
Journal of Mathematical Imaging and Vision, Springer Verlag, 2021, 63, pp.89-107
Journal of Mathematical Imaging and Vision, Springer Verlag, 2021, 63, pp.89-107. ⟨10.1007/s10851-020-00996-z⟩
Journal of Mathematical Imaging and Vision, 2021, 63 (1), pp.89-107. ⟨10.1007/s10851-020-00996-z⟩
J Math Imaging Vis
Journal of Mathematical Imaging and Vision, Springer Verlag, 2021, 63, pp.89-107
Journal of Mathematical Imaging and Vision, Springer Verlag, 2021, 63, pp.89-107. ⟨10.1007/s10851-020-00996-z⟩
Journal of Mathematical Imaging and Vision, 2021, 63 (1), pp.89-107. ⟨10.1007/s10851-020-00996-z⟩
J Math Imaging Vis
Optimal transport (OT) distances between probability distributions are parameterized by the ground metric they use between observations. Their relevance for real-life applications strongly hinges on whether that ground metric parameter is suitably ch
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::df2d3a35eee2d474cef51ecf24847c3c
http://arxiv.org/abs/1911.03117
http://arxiv.org/abs/1911.03117
Autor:
Gabriel Peyré, Marco Cuturi
Publikováno v:
Foundations and Trends in Machine Learning
Foundations and Trends in Machine Learning, Now Publishers, 2018, 11 (5-6), pp.355-206. ⟨10.1561/2200000073⟩
Foundations and Trends® in Machine Learning
Foundations and Trends in Machine Learning, Now Publishers, 2018, 11 (5-6), pp.355-206. ⟨10.1561/2200000073⟩
Foundations and Trends® in Machine Learning
Optimal transport (OT) theory can be informally described using the words of the French mathematician Gaspard Monge (1746-1818): A worker with a shovel in hand has to move a large pile of sand lying on a construction site. The goal of the worker is t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::622eb683a94504c5c7b08f99c0ff36d6
https://doi.org/10.1561/9781680835519
https://doi.org/10.1561/9781680835519