Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Leland McInnes"'
Publikováno v:
Neural computation, vol 33, iss 11
Neural Comput
Neural Comput
UMAP is a nonparametric graph-based dimensionality reduction algorithm using applied Riemannian geometry and algebraic topology to find low-dimensional embeddings of structured data. The UMAP algorithm consists of two steps: (1) computing a graphical
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::64003c116c0e2359d751c9a475b18798
https://escholarship.org/uc/item/6dc0b8c0
https://escholarship.org/uc/item/6dc0b8c0
Autor:
Mark P. Oxley, Stephen Jesse, Sergei V. Kalinin, Andrew R. Lupini, Ondrej Dyck, Xin Li, Leland McInnes, John Healy
Publikováno v:
npj Computational Materials, Vol 6, Iss 1, Pp 1-1 (2020)
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Publikováno v:
Solar Physics. 295
We present two new solar wind origin classification schemes developed independently using unsupervised machine learning. The first scheme aims to classify solar wind into three types: coronal-hole wind, streamer-belt wind, and ‘unclassified’ whic
Autor:
Mark P. Oxley, Andrew R. Lupini, Sergei V. Kalinin, Ondrej Dyck, John Healy, Stephen Jesse, Xin Li, Leland McInnes
Publikováno v:
npj Computational Materials, Vol 5, Iss 1, Pp 1-8 (2019)
Four-dimensional scanning transmission electron microscopy (4D-STEM) of local atomic diffraction patterns is emerging as a powerful technique for probing intricate details of atomic structure and atomic electric fields. However, efficient processing
Autor:
Leland McInnes
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030269791
GSI
GSI
Unsupervised learning is a broad topic in machine learning with many diverse sub-disciplines. Within the field of unsupervised learning we will consider three major topics: dimension reduction; clustering; and anomaly detection. We seek to use the la
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e4fd5249da5ab3fccdb7c0ac4af3f960
https://doi.org/10.1007/978-3-030-26980-7_35
https://doi.org/10.1007/978-3-030-26980-7_35
Autor:
Etienne Becht, Charles-Antoine Dutertre, Immanuel Kwok, Leland McInnes, John Healy, Florent Ginhoux, Evan W. Newell, Lai Guan Ng
Publikováno v:
Nature biotechnology.
Advances in single-cell technologies have enabled high-resolution dissection of tissue composition. Several tools for dimensionality reduction are available to analyze the large number of parameters generated in single-cell studies. Recently, a nonli
Autor:
John Healy, Leland McInnes
Publikováno v:
ICDM Workshops
We present an accelerated algorithm for hierarchical density based clustering. Our new algorithm improves upon HDBSCAN*, which itself provided a significant qualitative improvement over the popular DBSCAN algorithm. The accelerated HDBSCAN* algorithm
Publikováno v:
Journal of Open Source Software. 3:861
Autor:
David M. Riley, Leland McInnes
Publikováno v:
Journal of Algebra. 319:205-234
Let p be a prime number. A finite nilpotent Lie ring of characteristic a power of p is called finite-p. A pro-p Lie ring is an inverse limit of finite-p Lie rings. Pro-p Lie rings play a role in Lie theory similar to that played by pro-p groups in gr
Publikováno v:
The Journal of Open Source Software. 2:205