# vae_conv

**Repository Path**: haohan1997/vae_conv

## Basic Information

- **Project Name**: vae_conv
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-11-24
- **Last Updated**: 2021-11-24

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# vae_conv
Convolutional variational autoencoder in PyTorch

# Basic VAE Example

This is an improved implementation of the paper [Stochastic Gradient VB and the
Variational Auto-Encoder](http://arxiv.org/abs/1312.6114) by Kingma and Welling.
It uses ReLUs and the adam optimizer, instead of sigmoids and adagrad. These changes make the network converge much faster.

```bash
pip install -r requirements.txt
python main.py
```