1. This repository follows the great tutorial by [Eric Jang on normalizing flows.](https://github.com/ericjang/normalizing-flows-tutorial)
### Implementation
2. Repository will update itself as variations of normalizing flows are implemented.
3. Performance evaluation will be done at the end of the project.
* Parameters
4. Implementations are in Jupyter Notebook. Articles on normalizing flows, possibly with modular Python scripts of notebooks, will be added on the fly.
* number of hidden layers
* base distribution
* bijector count
* neuron size
* optimizers
* iteration count
### Performance Evaluation
* Performance evaluation will be done at the end of the project.
* convergence time
* correctness
* robustness
### Reference
* This repository is inspired by the great tutorial by [Eric Jang on normalizing flows](https://github.com/ericjang/normalizing-flows-tutorial) and [TensorFlow probability docs.](https://www.tensorflow.org/probability)
