https://github.com/sjchoi86/advanced-tensorflow
Little More Advanced TensorFlow Implementations
https://github.com/sjchoi86/advanced-tensorflow
char-rnn gan rnn-tensorflow tensorflow tensorflow-implementations
Last synced: 3 months ago
JSON representation
Little More Advanced TensorFlow Implementations
- Host: GitHub
- URL: https://github.com/sjchoi86/advanced-tensorflow
- Owner: sjchoi86
- Created: 2016-12-31T04:19:39.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2017-11-29T04:40:35.000Z (over 7 years ago)
- Last Synced: 2025-03-31T10:11:12.482Z (3 months ago)
- Topics: char-rnn, gan, rnn-tensorflow, tensorflow, tensorflow-implementations
- Language: Jupyter Notebook
- Size: 55.7 MB
- Stars: 371
- Watchers: 29
- Forks: 115
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Advanced TensorFlow
Collection of (Little More + Refactored) Advanced TensorFlow Implementations.
Try my best to implement algorithms with a single Jupyter Notebook.
### [AutoEncoder](https://github.com/sjchoi86/advanced-tensorflow/tree/master/ae)
- Denoising AutoEncoder
- Convolutional AutoEncoder (using deconvolution)
- Variational AutoEncoder
### [Adversarial Variational Bayes](https://github.com/sjchoi86/advanced-tensorflow/tree/master/avb)
- AVB on 2-dimensional Toy Example
### [Basics](https://github.com/sjchoi86/advanced-tensorflow/tree/master/basic)
- Basic Classification (MLP and CNN)
- Custom Dataset Generation
- Classification (MLP and CNN) using Custom Dataset
- OOP Style Implementation of MLP and CNN
### [Class Activation Map](https://github.com/sjchoi86/advanced-tensorflow/tree/master/cam)
- Pretrained Network Usage with TF-SLIM
- Class Activation Map with Pretrained Network
### [Char-RNN](https://github.com/sjchoi86/advanced-tensorflow/tree/master/char-rnn)
- Preprocess Linux Kernel Sources
- Train and Sample with Char-RNN
### [Domain Adaptation](https://github.com/sjchoi86/advanced-tensorflow/tree/master/dann)
- Domain Adversarial Neural Network with Gradient Reversal Layer
### [Generative Adversarial Network](https://github.com/sjchoi86/advanced-tensorflow/tree/master/dcgan)
- Deep Convolutional Generative Adversarial Network with MNIST
### [Mixture Density Network](https://github.com/sjchoi86/advanced-tensorflow/tree/master/mdn)
- Mixture Density Network
- Heteroscedastic Mixture Density Network
### [Reinforcement Learning](https://github.com/sjchoi86/advanced-tensorflow/tree/master/rl)
- Model Based RL (Value Iteration and Policy Iteration)
### [TF-SLIM](https://github.com/sjchoi86/advanced-tensorflow/tree/master/mnist)
- MNIST Classification with TF-SLIM
### [Super Resolution](https://github.com/sjchoi86/advanced-tensorflow/tree/master/srgan)
- Super-resolution with Generative Adversarial Network
## Requirements
- Python-2.7
- TensorFlow-1.0.1
- SciPy
- MatplotLib
- Jupyter Notebook