Zobrazeno 1 - 2
of 2
pro vyhledávání: '"Shen, Xinwei"'
In a modern power system, real-time data on power generation/consumption and its relevant features are stored in various distributed parties, including household meters, transformer stations and external organizations. To fully exploit the underlying
Externí odkaz:
http://arxiv.org/abs/2201.02783
Publikováno v:
Journal of Machine Learning Research 23(241): 1-55, 2022
This paper proposes a Disentangled gEnerative cAusal Representation (DEAR) learning method under appropriate supervised information. Unlike existing disentanglement methods that enforce independence of the latent variables, we consider the general ca
Externí odkaz:
http://arxiv.org/abs/2010.02637