junliangma's repositories
pseudo_label-pytorch
The Simple and Efficient Semi-Supervised Learning Method for Deep Neural Networks
DPC-DLP
Dynamic Graph-Based Label Propagation for Density Peaks Clustering
Active-GBSSL
This is a project of my paper related to active learning and graph based semi-supervised learning, which is published on ICME 2014. The project is written by matlab
GraphSAGE
Representation learning on large graphs using stochastic graph convolutions.
semi_supervised_wrapper_method
A semi supervised wrapper method better than Label Propagation on Enron data set.
MachineLearning
Basic Machine Learning and Deep Learning
Graph-Clustering
Implemented Label Propagation Algorithm of Graph Clustering in python, which was later used as an application for providing friend suggestions in any social networking site.This was done in group of 4.
tensorflow-tutorial
Example TensorFlow codes and Caicloud TensorFlow as a Service dev environment.
PSP-CRF
Improving Semantic Image Segmentation with a Probabilistic Superpixel-based Dense Conditional Random Field
semi_supervised
Combining Graph Laplacians for Semi-Supervised Learning
semi-supervised-satellite-image-segmentation
Exploration of using semi-supervised pre-training to improve convolutional neural network image segmentation performance on satellite imagery
SSL_lib
Methods for semi-supervised learning on graphs
gunrock
High-Performance Graph Primitives on GPUs
PG-Learn
An efficient algorithm to learn graph for semi-supervised learning
fashion-mnist
A MNIST-like fashion product database. Benchmark :point_right:
gSSL
Graph SSL, biased random walk, bridgeness centrality
semantic-segmentation
Semantic instance segmentation of specimen images using semi-supervised learning
tf-propagation
A TensorFlow Label Propagation library
Semi-Supervised-Image-Classification
The code written on the understanding of the paper: "Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples"
LPLNS
Predicting microRNA-disease associations using label propagation based on linear neighborhood similarity
hangzhou_house_knowledge
2017年买房经历总结出来的买房购房知识分享给大家，希望对大家有所帮助。买房不易，且买且珍惜。Sharing the knowledge of buy an own house that according to the experience at hangzhou in 2017 to all the people. It's not easy to buy a own house, so I hope that it would be useful to everyone.
awesome-public-datasets
A topic-centric list of high-quality open datasets in public domains. By everyone, for everyone!
LabelPropagation-1
A simple implementation of Label Propagation.
semi-supervised-pytorch
Implementations of different VAE-based semi-supervised and generative models in PyTorch