• Stars
    star
    11
  • Rank 1,694,829 (Top 34 %)
  • Language
    Jupyter Notebook
  • License
    MIT License
  • Created almost 8 years ago
  • Updated almost 8 years ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

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

More Repositories

1

vae-clustering

Unsupervised clustering with (Gaussian mixture) VAEs
Jupyter Notebook
287
star
2

dirt-t

A DIRT-T Approach to Unsupervised Domain Adaptation (ICLR 2018)
Python
174
star
3

nn-bayesian-optimization

We use a modified neural network instead of Gaussian process for Bayesian optimization.
Python
105
star
4

cvae

Conditional variational autoencoder implementation in Torch
Jupyter Notebook
102
star
5

tensorsketch

A lightweight library for tensorflow 2.0
Python
66
star
6

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.
Lua
62
star
7

micro-projects

A collection of small code snippets for learning how to code
Jupyter Notebook
58
star
8

tensorbayes

Deep variational inference in tensorflow
Python
56
star
9

began

Boundary equilibrium GAN implementation in Tensorflow
Python
15
star
10

kaos

Deep variational inference library for Keras
Python
15
star
11

fast-style-transfer

Fast style transfer in TensorFlow
Python
14
star
12

tensorflow-gp

Implementation of gaussian processes and bayesian optimization in tensorflow
Jupyter Notebook
11
star
13

variational-autoencoder

Basic implementation of variational autoencoders in Torch
Jupyter Notebook
9
star
14

acgan-biased

Experiments verifying that AC-GAN downsamples points near decision boundary (NIPS BDL 2017)
Python
9
star
15

deep-generative-models

Deep generative models in Tensorflow
Python
6
star
16

ConvFeFe

The best neural network
Python
4
star
17

bcde

Bottleneck Conditional Density Estimation (ICML 2017)
Python
4
star
18

vda-hax

Simple tricks to improve visual domain adaptation for MNIST -> SVHN
Python
3
star