Unsupervised Learning Universal Critical Behavior via the Intrinsic Dimension
The identification of universal properties from minimally processed data sets is one goal of machine learning techniques applied to statistical physics. Here, we study how the minimum number of variables needed to accurately describe the important features of a data set—the intrinsic dimension (I_{d...
Guardado en:
Autores principales: | T. Mendes-Santos, X. Turkeshi, M. Dalmonte, Alex Rodriguez |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
American Physical Society
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/022d2f65518840b0bedc492738de178e |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Benchmark and application of unsupervised classification approaches for univariate data
por: Maria El Abbassi, et al.
Publicado: (2021) -
Broadband Terahertz Probes of Anisotropic Magnetoresistance Disentangle Extrinsic and Intrinsic Contributions
por: Lukáš Nádvorník, et al.
Publicado: (2021) -
Intrinsic Anomalous Nernst Effect Amplified by Disorder in a Half-Metallic Semimetal
por: Linchao Ding, et al.
Publicado: (2019) -
Strain tunable intrinsic ferromagnetic in 2D square CrBr2
por: Fei Li, et al.
Publicado: (2021) -
Critical behavior in interdependent spatial spreading processes with distinct characteristic time scales
por: Piergiorgio Castioni, et al.
Publicado: (2021)