A random collection of things I'm experimenting with, usually in the form of notebooks.
Some blog posts relating to things in here:
notebooks/variational-autoencoder.ipynb: http://bjlkeng.github.io/posts/variational-autoencoders/notebooks/variational_autoencoder-svhn: http://bjlkeng.github.io/posts/a-variational-autoencoder-on-the-svnh-dataset/notebooks/vae-semi_supervised_learning: http://bjlkeng.github.io/posts/semi-supervised-learning-with-variational-autoencoders/notebooks/vae-inverse_autoregressive_flows: http://bjlkeng.github.io/posts/variational-autoencoders-with-inverse-autoregressive-flows/notebooks/masked_autoencoders: http://bjlkeng.github.io/posts/autoregressive-autoencoders/notebooks/label_refinery: http://bjlkeng.github.io/posts/label-refinery/notebooks/vae-resnet: http://bjlkeng.github.io/posts/residual-networks/notebooks/universal_resnet: http://bjlkeng.github.io/posts/universal-resnet-the-one-neuron-approximator/notebooks/vae-importance_sampling: http://bjlkeng.github.io/posts/importance-sampling-and-estimating-marginal-likelihood-in-variational-autoencoders/notebooks/pixel_cnn: http://bjlkeng.github.io/posts/pixelcnn/ans: https://bjlkeng.github.io/posts/lossless-compression-with-asymmetric-numeral-systems/hmc: https://bjlkeng.github.io/posts/hamiltonian-monte-carlo/