Rui Shu

vae-clustering. Unsupervised clustering with (Gaussian mixture) VAEs

dirt-t. A DIRT-T Approach to Unsupervised Domain Adaptation (ICLR 2018)

nn-bayesian-optimization. We use a modified neural network instead of Gaussian process for Bayesian optimization.

cvae. Conditional variational autoencoder implementation in Torch

tensorsketch. A lightweight library for tensorflow 2.0

vae-experiments. Code for some of the experiments I did with variational autoencoders on multi-modality and atari video prediction. Atari video prediction is work-in-progress.

tensorbayes. Deep variational inference in tensorflow

micro-projects. A collection of small code snippets for learning how to code

kaos. Deep variational inference library for Keras

began. Boundary equilibrium GAN implementation in Tensorflow

fast-style-transfer. Fast style transfer in TensorFlow

one-bit-vae. A silly and weirdly useful experiment where I attempt to encode one bit of information with a VAE

tensorflow-gp. Implementation of gaussian processes and bayesian optimization in tensorflow

variational-autoencoder. Basic implementation of variational autoencoders in Torch

acgan-biased. Experiments verifying that AC-GAN downsamples points near decision boundary (NIPS BDL 2017)

deep-generative-models. Deep generative models in Tensorflow

ConvFeFe. The best neural network

bcde. Bottleneck Conditional Density Estimation (ICML 2017)

real-nvp-pytorch. Real NVP PyTorch a Minimal Working Example

vda-hax. Simple tricks to improve visual domain adaptation for MNIST -> SVHN