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# Sandbox

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/

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