DDE-1/Generative-learning.md

@@ -6,6 +6,11 @@ _C. Ates_
 
 ...
 
+
+### VAE Examples
+
+* [Density Estimation: Variational Autoencoders](http://ruishu.io/2018/03/14/vae/)
+
 ## Generative Adversarial Networks (GANs)
 
 ...
@@ -29,6 +34,10 @@ _C. Ates_
 * [GANs with Keras and TensorFlow](https://www.pyimagesearch.com/2020/11/16/gans-with-keras-and-tensorflow/)
 * [GANs with Python: Number generator](https://stackabuse.com/introduction-to-gans-with-python-and-tensorflow/)
 * [Image-to-Image Translation](https://phillipi.github.io/pix2pix/)
+* [Collection of Keras implementations](https://github.com/eriklindernoren/Keras-GAN)
+* [Fantastic GANs and where to find them](https://guimperarnau.com/blog/2017/03/Fantastic-GANs-and-where-to-find-them)
+* [GAN applications and code demonstrations](https://github.com/nashory/gans-awesome-applications)
+
 
 #### Music related
 
@@ -39,7 +48,7 @@ _C. Ates_
 * [Using TensorFlow 2.0 to Compose Music](https://www.datacamp.com/community/tutorials/using-tensorflow-to-compose-music)
 
 
-#### Colab notebooks:
+#### Tutorials and Colab notebooks:
 
 * [Making music with Magenta](https://colab.research.google.com/notebooks/magenta/hello_magenta/hello_magenta.ipynb)
 * [style gan](https://github.com/jeffheaton/present/blob/master/youtube/style_gan.ipynb)
@@ -48,7 +57,12 @@ _C. Ates_
 * [TF DCGAN](https://www.tensorflow.org/tutorials/generative/dcgan)
 * [pix2pix](https://github.com/bnsreenu/python_for_microscopists/blob/master/252_generating_realistic_scientific_images_using_pix2pix/pix2pix_model.py)
 * [248-cifar_GAN](https://github.com/bnsreenu/python_for_microscopists/blob/master/248_keras_implementation_of_GAN/248-cifar_GAN.py)
-
+* [Pix2Pix GAN for Image-to-Image Translation](https://machinelearningmastery.com/how-to-develop-a-pix2pix-gan-for-image-to-image-translation/)
+* [How to Develop a CycleGAN for Image-to-Image Translation with Keras](https://machinelearningmastery.com/cyclegan-tutorial-with-keras/)
+* [Wasserstein Generative Adversarial Network (WGAN)](https://machinelearningmastery.com/how-to-code-a-wasserstein-generative-adversarial-network-wgan-from-scratch/)
+* [Tensorflow implementation of WassersteinGan paper](https://github.com/Mohammad-Rahmdel/WassersteinGAN-Tensorflow)
+* [Application to Image Deblurring](https://medium.com/sicara/keras-generative-adversarial-networks-image-deblurring-45e3ab6977b5)
+* [Applications of GAN](https://jonathan-hui.medium.com/gan-some-cool-applications-of-gans-4c9ecca35900)
 
 ## Research papers:
 
@@ -63,6 +77,13 @@ _C. Ates_
 * [1D Generative Adversarial Network From Scratch](https://machinelearningmastery.com/how-to-develop-a-generative-adversarial-network-for-a-1-dimensional-function-from-scratch-in-keras/)
 * []()
 
+### Time series examples
+
+* [Time Series Generation with Recurrent Conditional GANs](https://arxiv.org/abs/1706.02633)
+* [Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs](https://github.com/ratschlab/RGAN)
+* [Anomaly Detection for Time Series Data with GAN](https://arxiv.org/pdf/1901.04997.pdf); [code](https://github.com/LiDan456/MAD-GANs)
+* [Synthetic Time Series Data - Trading](https://stefan-jansen.github.io/machine-learning-for-trading/21_gans_for_synthetic_time_series/#implementing-timegan-using-tensorflow-2)
+
 ### Science applications
 
 * [Failure Prediction](https://arxiv.org/abs/1910.02034)