- CNN_MNIST_alternative.ipynb: demo to use Tensorflow & Keras to develop a simple CNN
- Flax_MNIST.ipynb: an introducton to the JAX Neural Net lib (FLAX)
- MNIST_whyCNN.ipynb: This notebook explores the MNIST dataset (digits by Y. LeCun) to highlight the surprising power of neural networks.
- Standardizing.ipynb: demo how to get a normal distribution (standardization) using BOX-COX transformation (scipy) as well as Normalizing Flows (lightweight normalizing-flows Pytorch lib.)
- Sampling_simple_JAX.ipynb, Test_JAX_FLows.ipynb: nb on how to use distrax JAX lib for distribution sampling using Bijectors.
- Test_AR_NFLows.ipynb, Test_MADE_NVP_MAF_IAF.ipynb,Toy_Flow_cubic.ipynb: nbs on how to use TensorFlow Bijectors & Normalizing Flows
- Test_Flow.ipynb: a more complete nb on Normalizing Flows
- Demo_SBI_HMC.ipynb: demo to use Numpyro lib. to get a model parameters using HMC sampling, and SBI lib. to setup a Simulation Based Inference forward modeling with different methods.