336 Open source projects that are alternatives of or similar to Awesome Graph Classification

A list of data mining and machine learning papers that I implemented in 2019.

The reference implementation of FEATHER from the CIKM '20 paper "Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric Models".

An implementation of "Fusing Structure and Content via Non-negative Matrix Factorization for Embedding Information Networks".

A distributed graph deep learning framework.

A lightweight implementation of Walklets from "Don't Walk Skip! Online Learning of Multi-scale Network Embeddings" (ASONAM 2017).

An alternative implementation of Recursive Feature and Role Extraction (KDD11 & KDD12)

The official PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing" (WebConf '21)

Clean & Documented TF2 implementation of "An end-to-end deep learning architecture for graph classification" (M. Zhang et al., 2018).

Graph Embedding via Frequent Subgraphs

links to conference publications in graph-based deep learning

My implementation of "Hierarchical Attention Networks for Document Classification" in Keras

Representation learning-based graph alignment based on implicit matrix factorization and structural embeddings

A sparsity aware implementation of "Alternating Direction Method of Multipliers for Non-Negative Matrix Factorization with the Beta-Divergence" (ICASSP 2014).

A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which appeared in The International Workshop on Self-Supervised Learning for the Web (SSL'21) @ the Web Conference 2021 (WWW'21).

A python package for graph kernels, graph edit distances, and graph pre-image problem.

An implementation of "Community Preserving Network Embedding" (AAAI 2017)

A curated list of community detection research papers with implementations.

Graph Attention Networks (https://arxiv.org/abs/1710.10903)

A Context-aware Visual Attention-based training pipeline for Object Detection from a Webpage screenshot!

Implementation and experiments of graph embedding algorithms.

Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)

OpenANE: the first Open source framework specialized in Attributed Network Embedding. The related paper was accepted by Neurocomputing. https://doi.org/10.1016/j.neucom.2020.05.080

Code and resources on scalable and efficient Graph Neural Networks

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

Tri-Party Deep Network Representation, IJCAI-16

Quaternion Graph Neural Networks (ACML 2021) (Pytorch and Tensorflow)

Transformer of "Attention Is All You Need" (Vaswani et al. 2017) by Chainer.

Implementation of Linformer for Pytorch

Implementation of TransGanFormer, an all-attention GAN that combines the finding from the recent GanFormer and TransGan paper

PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).

A TensorFlow Implementation of the Transformer: Attention Is All You Need

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

Applied Deep Learning (2019 Spring) @ NTU

Code for the paper "VistaNet: Visual Aspect Attention Network for Multimodal Sentiment Analysis", AAAI'19

Code for our paper "Multi-scale Guided Attention for Medical Image Segmentation"

Using Residual Attention Networks to diagnose retinal diseases in medical images

Attention-Based Guided Structured Sparsity of Deep Neural Networks

End-to-end ASR/LM implementation with PyTorch

Keras implementation of the graph attention networks (GAT) by Veličković et al. (2017; https://arxiv.org/abs/1710.10903)

Implementation of TimeSformer from Facebook AI, a pure attention-based solution for video classification

a simple and complete pytorch implementation of neural machine translation system

一些不同的Attention机制代码

A Pytorch Implementation of "Attention is All You Need" and "Weighted Transformer Network for Machine Translation"

Pytorch implementation of "Dynamic Coattention Networks For Question Answering"

Model Compression—YOLOv3 with multi lightweight backbones(ShuffleNetV2 HuaWei GhostNet), attention, prune and quantization

Code for CIKM'18 paper, Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects.

🔖 An Attention Layer in Keras

PyTorch Implementation of GraphTSNE, ICLR’19

📃 **Unofficial** PyTorch Implementation of DA-RNN (arXiv:1704.02971)

Drug Similarity Integration Through Attentive Multi-view Graph Auto-Encoders (IJCAI 2018)

My implementation of the original transformer model (Vaswani et al.). I've additionally included the playground.py file for visualizing otherwise seemingly hard concepts. Currently included IWSLT pretrained models.

Code for PaperRobot: Incremental Draft Generation of Scientific Ideas

基于seq2seq模型的简单对话系统的tf实现，具有embedding、attention、beam_search等功能，数据集是Cornell Movie Dialogs

Official repository for "Learning Enriched Features for Real Image Restoration and Enhancement" (ECCV 2020). SOTA results for image denoising, super-resolution, and image enhancement.

A Matlab benchmarking toolbox for kernel adaptive filtering

An ultra-fast, GPU-based large graph embedding algorithm utilizing a novel coarsening algorithm requiring not more than a single GPU.

Vídeos e códigos do Universo Discreto ensinando o fundamental de Machine Learning em Python. Para mais detalhes, acompanhar a playlist listada.

[GRL+ @ ICML 2020] PyTorch implementation for "Deep Graph Contrastive Representation Learning" (https://arxiv.org/abs/2006.04131v2)

PyTorch Implementation of "Monotonic Chunkwise Attention" (ICLR 2018)

End-to-End speech recognition implementation base on TensorFlow (CTC, Attention, and MTL training)