Cargando…
Temperature based Restricted Boltzmann Machines
Restricted Boltzmann machines (RBMs), which apply graphical models to learning probability distribution over a set of inputs, have attracted much attention recently since being proposed as building blocks of multi-layer learning systems called deep belief networks (DBNs). Note that temperature is a...
Autores principales: | Li, Guoqi, Deng, Lei, Xu, Yi, Wen, Changyun, Wang, Wei, Pei, Jing, Shi, Luping |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4725829/ https://www.ncbi.nlm.nih.gov/pubmed/26758235 http://dx.doi.org/10.1038/srep19133 |
Ejemplares similares
-
Privacy-Preserving Restricted Boltzmann Machine
por: Li, Yu, et al.
Publicado: (2014) -
Thermodynamics of the Ising Model Encoded in Restricted Boltzmann Machines
por: Gu, Jing, et al.
Publicado: (2022) -
Entropy, Free Energy, and Work of Restricted Boltzmann Machines
por: Oh, Sangchul, et al.
Publicado: (2020) -
Predicting drug-target interactions using restricted Boltzmann machines
por: Wang, Yuhao, et al.
Publicado: (2013) -
An Underwater Acoustic Target Recognition Method Based on Restricted Boltzmann Machine
por: Luo, Xinwei, et al.
Publicado: (2020)