Continuous hierarchical representations with poincaré Variational Auto-Encoder
The Variational Auto-Encoder (VAE) is a popular method for learning a generative model and embeddings of the data. Many real datasets are hierarchically structured. However, traditional VAEs map data in a Euclidean latent space which cannot efficiently embed tree-like structures. Hyperbolic spaces w...
Main Authors: | Mathieu,E, Le Lan, C, Maddison, CJ, Tomioka, R, Teh, YW |
---|---|
格式: | Conference item |
语言: | English |
出版: |
Curran Associates
2019
|
相似书籍
-
Partial disentanglement of hierarchical variational auto‐encoder for texture synthesis
由: Marek Jakab, et al.
出版: (2020-12-01) -
VAEEG: Variational auto-encoder for extracting EEG representation
由: Tong Zhao, et al.
出版: (2024-12-01) -
Representation learning by hierarchical ELM auto‐encoder with double random hidden layers
由: Rui Li, et al.
出版: (2019-06-01) -
Hamiltonian Variational Auto-Encoder
由: Caterini, A, et al.
出版: (2019) -
Conditional Variational AutoEncoder based on Stochastic Attacks
由: Gabriel Zaid, et al.
出版: (2023-03-01)