jiamingz1996 Goto Github PK
Name: Jiamigz1996
Type: User
Company: Hebut
Bio: PhD Student
Location: TianJin
Name: Jiamigz1996
Type: User
Company: Hebut
Bio: PhD Student
Location: TianJin
AOAM: Automatic Optimization of Adjacency Matrix for Graph Convolutional Network
A curated list of network embedding techniques.
center loss for face recognition
AISTATS 2019: Confidence-based Graph Convolutional Networks for Semi-Supervised Learning
cvpr2020 source code
Deeper insights into graph convolutional networks for semi-supervised learning
Official PyTorch implementation of "Towards Deeper Graph Neural Networks" [KDD2020]
code of DeepGWC: A Deep Graph Wavelet Convolutional Neural Network for Semi-supervised Node Classification
The code of Graph Attention Networks for Cora, Citeseer, Pubmed and PPI
AAAI'21: Data Augmentation for Graph Neural Networks
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training
PyTorch implementation of "Simple and Deep Graph Convolutional Networks"
PyTorch implementation of "Graph Convolutional Networks for Graphs Containing Missing Features"
A pytorch implementation of "Propagation is All You Need: A New Framework for Representation Learning and Classifier Training on Graphs".
Must-read papers on graph neural networks (GNN)
links to conference publications in graph-based deep learning
GraphGallery is a gallery for benchmarking Graph Neural Networks (GNNs) with TensorFlow 2.x and PyTorch backend.
This is the official implementation for "Do Transformers Really Perform Bad for Graph Representation?".
Source code of GResNet
:octocat: 分享 GitHub 上有趣、入门级的开源项目
NeurIPS 2019: HyperGCN: A New Method of Training Graph Convolutional Networks on Hypergraphs
AISTATS 2019: Lovász Convolutional Networks
[WWW 2021 GLB] New Benchmarks for Learning on Non-Homophilous Graphs
[NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods
Must-read papers on network representation learning (NRL) / network embedding (NE)
现有聚类算法面向高维稀疏数据多未考虑类簇可重叠和离群点的存在,导致聚类效果不理想。针对此,提出一种可重叠子空间K-Means聚类算法(An Overlapping Subspace K-Means Clustering Algorithm, OS-K-Means)。给出类簇子空间计算策略,在聚类过程中动态更新每个类簇的属性子空间,并定义合理的约束函数指导聚类过程,从而实现类簇的可重叠性与寻找离群点的效果。具体地,定义合理的目标函数对传统的K-Means算法进行修正,利用熵权约束分别计算每个类簇中每个维度的权重,使用权重值来标识对不同类簇中维度的相对重要性,并加入对重叠程度和离群值数量控制的参数。
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.