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The Wayback Machine - https://web.archive.org/web/20200626162545/https://github.com/topics/cvae
Here are
24 public repositories
matching this topic...
Collection of generative models in Tensorflow
Updated
Jul 21, 2018
Python
Tensorflow Implementation of Knowledge-Guided CVAE for dialog generation ACL 2017. It is released by Tiancheng Zhao (Tony) from Dialog Research Center, LTI, CMU
Updated
Nov 26, 2018
OpenEdge ABL
Variational Autoencoder and Conditional Variational Autoencoder on MNIST in PyTorch
Updated
Apr 3, 2019
Python
Tensorflow implementation of conditional variational auto-encoder for MNIST
Updated
Apr 25, 2017
Python
DESIRE: Distant Future Prediction in Dynamic Scenes with Interacting Agents
Updated
Oct 22, 2018
Python
Conditional Out-of-Sample prediction
Updated
May 15, 2020
Jupyter Notebook
pytorch implementation Variational Autoencoder and Conditional Variational Autoencoder
Updated
Oct 18, 2018
Jupyter Notebook
Implementation of the Conditional Variational Auto-Encoder (CVAE) in Tensorflow
Updated
Feb 14, 2018
Python
Updated
Oct 24, 2018
Jupyter Notebook
The implementation of Gumbel softmax reparametrization trick for discrete VAE
Updated
Apr 9, 2018
Python
CVAE for dialog generation
Updated
Jan 23, 2018
Python
Variational Auto Encoders (VAEs), Generative Adversarial Networks (GANs) and Generative Normalizing Flows (NFs) and are the most famous and powerful deep generative models.
Updated
Jan 14, 2020
Python
Conditional Variational AutoEncoder (CVAE) PyTorch implementation
Updated
Nov 29, 2019
Python
a collection of variational autoencoders
Updated
Nov 30, 2019
Python
CVAE-GPT2 open-domain chatbot
Updated
May 29, 2020
Python
VAE and CVAE pytorch implement based on MNIST
Updated
Nov 5, 2019
Jupyter Notebook
PyTorch implementations of Variational Autoencoder and Conditional Variational Autoencoder
Updated
Jul 11, 2019
Jupyter Notebook
Implementations of deep learning algorithms
Updated
Jan 8, 2019
Jupyter Notebook
Updated
Mar 11, 2019
Jupyter Notebook
A PyTorch implementation of neural dialogue system using conditional variational autoencoder (CVAE)
CVAE implementation on MNIST dataset using PyTorch
Updated
Jun 6, 2020
Python
Updated
Mar 29, 2019
Python
Bayesian based machine learning implementations (GMM, VAE & conditional VAE).
Updated
Feb 20, 2020
Jupyter Notebook
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While using the magnitude CQT instead of the magnitude FFT, take care to modify the network layer sizes accordingly.
For the other modifications, refer to the comments in the appropriate code.
Thank you.