Variational Inference

Introduced by Cemgil et al. in Autoencoding Variational Autoencoder

Source: Autoencoding Variational Autoencoder

Paper	Code	Results	Date	Stars

Task	Papers	Share
Uncertainty Quantification	30	6.82%
Decoder	17	3.86%
Decision Making	13	2.95%
Density Estimation	12	2.73%
Classification	10	2.27%
Time Series Analysis	10	2.27%
Federated Learning	9	2.05%
Disentanglement	9	2.05%
Causal Discovery	9	2.05%

This feature is experimental; we are continuously improving our matching algorithm.

Component	Type	Add Remove
🤖 No Components Found	You can add them if they exist; e.g. Mask R-CNN uses RoIAlign