dengwanxia1991

gcn

Implementation of Graph Convolutional Networks in TensorFlow

prototypical-networks

Code for the NeurIPS 2017 Paper "Prototypical Networks for Few-shot Learning"

semi-supervised-pytorch

Implementations of various VAE-based semi-supervised and generative models in PyTorch

Beta-VAE

Pytorch implementation of β-VAE

DEC-keras

Keras implementation for Deep Embedding Clustering (DEC)

disentangled-representation-papers

A curated list of research papers related to learning disentangled representations

SKNet

try to implement the CVPR 2019 paper "Selective Kernel Networks" by PyTorch

InfoGAN-PyTorch

PyTorch Implementation of InfoGAN

L2C

Learning to Cluster. A deep clustering strategy.

GMVAE

Implementation of Gaussian Mixture Variational Autoencoder (GMVAE) for Unsupervised Clustering

pytorch_compact_bilinear_pooling

Compact Bilinear Pooling for PyTorch

CompactBilinearPooling-Pytorch

A Pytorch Implementation for Compact Bilinear Pooling.

Deep-K-Means-pytorch

[ICML 2018] "Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions"

GeneGAN

GeneGAN: Learning Object Transfiguration and Attribute Subspace from Unpaired Data

blinear-cnn-faster

A Faster PyTorch implementation of bilinear CNN for fine-grained image recognition

ss-gan

Style and Structure GAN (ECCV 2016)

PADA

Code release for "Partial Adversarial Domain Adaptation" (ECCV 2018)

kmeans_pytorch

pytorch implementation of basic kmeans algorithm(lloyd method with forgy initialization) with gpu support

Transferable-Adversarial-Training

Code release for Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers (ICML2019)

NNclustering

The demo code for "Neural network-based clustering using pairwise constraints" (http://arxiv.org/abs/1511.06321)

openset-DA

Code for 'Open Set Domain Adaptation by Backpropagation'

Separate_to_Adapt

Code release for Separate to Adapt: Open Set Domain Adaptation via Progressive Separation (CVPR 2019)

OSRAAE

Open-set Recognition with Adversarial Autoencoders

Open-Set-Domain-Adaptation-for-Hyperspectral-Image-Classification-Using-Generative-Adversarial-Netwo

The Noval approach for dealing with hyperspectral images with the help of openset domain adaptatin and generative adversarial network.

Autoencoder-Clustering

Replication of "Auto-encoder Based Data Clustering" Song et al

Bilinear-CNN

A pytorch implementation of bilinear CNN for fine-grained image recognition

pooling_time

Low rank bilinear pooling in torch and keras

GSFL-Net

pytorch-kmeans-init

Weight initialization of deep networks using k-means clustering

domAdapt_imageclef2014

Applying the DAM Framework to the ImageCLEF 2014 domain adaptation challenge.