A Collection of Variational Autoencoders (VAE) in PyTorch.
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Updated
Jun 13, 2024 - Python
A Collection of Variational Autoencoders (VAE) in PyTorch.
Easy generative modeling in PyTorch.
Code for the paper "VAE with a VampPrior", J.M. Tomczak & M. Welling
Official implementation of Dynamical VAEs
Voxel-Based Variational Autoencoders, VAE GUI, and Convnets for Classification
Deep and Machine Learning for Microscopy
Variational Graph Recurrent Neural Networks - PyTorch
This repository tries to provide unsupervised deep learning models with Pytorch
Ladder Variational Autoencoders (LVAE) in PyTorch
Deep active inference agents using Monte-Carlo methods
Code for the paper "Improving Variational Auto-Encoders using Householder Flow" (https://arxiv.org/abs/1611.09630)
Computer code collated for use with Artificial Intelligence Engines book by JV Stone
Code for the Paper: "Conditional Variational Capsule Network for Open Set Recognition", Y. Guo, G. Camporese, W. Yang, A. Sperduti, L. Ballan, ICCV, 2021.
Generator loss to reduce mode-collapse and to improve the generated samples quality.
[Pytorch] Generative retrieval model based on RQ-VAE from "Recommender Systems with Generative Retrieval"
Official PyTorch implementation of A Quaternion-Valued Variational Autoencoder (QVAE).
PyTorch re-implementation of [Structured Inference Networks for Nonlinear State Space Models, AAAI 17]
Orgainzed Digital Intelligent Network (O.D.I.N)
implement Deep Feature Consisten Variational Autoencoder in Tensorflow
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