Keras implementation of NADE models
-
Updated
Jan 4, 2018 - Python
Keras implementation of NADE models
基于单层神经网络的自回归生成模型,包含多种数据类型的概率建模、模型训练、样本生成与结果可视化。
PyTorch implementations of FVSBN, NADE, and MADE — foundational autoregressive density estimators for binarised MNIST — with a vectorised NADE training loop, a 15-run hyper-parameter sweep, and publication-quality architecture figures.
Comparative analysis of Variational Autoencoders (VAE) and Neural Autoregressive Distribution Estimator (NADE) across image, text, and speech modalities using PyTorch.
To associate your repository with the nade topic, visit your repo's landing page and select "manage topics."