深度学习入门教程, 优秀文章, Deep Learning Tutorial

该仓库主要记录 NLP 算法工程师相关的顶会论文研读笔记

StellarGraph - Machine Learning on Graphs

PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)

A distributed graph deep learning framework.

Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)

A work-in-progress PlayStation 4 emulator.

《深入浅出图神经网络：GNN原理解析》配套代码

A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow.

An index of recommendation algorithms that are based on Graph Neural Networks. (TORS)

Next RecSys Library

Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).

resources for graph convolutional networks （图卷积神经网络相关资源）

Implementation and experiments of graph neural netwokrs, like gcn,graphsage,gat,etc.

A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation" (WSDM 2019).

A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).

常用的语义分割架构结构综述以及代码复现

Learning to Cluster Faces (CVPR 2019, CVPR 2020)

More readable and flexible yolov5 with more backbone(gcn, resnet, shufflenet, moblienet, efficientnet, hrnet, swin-transformer, etc) and (cbam，dcn and so on), and tensorrt

The PyTorch implementation of STGCN.

A repository of pretty cool datasets that I collected for network science and machine learning research.

A PyTorch implementation of "Graph Wavelet Neural Network" (ICLR 2019)

Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers [CVPR 2021]

[ICLR 2020; IPDPS 2019] Fast and accurate minibatch training for deep GNNs and large graphs (GraphSAINT: Graph Sampling Based Inductive Learning Method).

An implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019).

Some TrafficFlowForecasting Solutions(交通流量预测解决方案)

A PyTorch implementation of "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019).

Code for CVPR'19 paper Linkage-based Face Clustering via GCN

Hierarchical Graph Pooling with Structure Learning

1. Use BERT, ALBERT and GPT2 as tensorflow2.0's layer. 2. Implement GCN, GAN, GIN and GraphSAGE based on message passing.