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Yuexin Li's Projects

ai-edu icon ai-edu

AI education materials for Chinese students, teachers and IT professionals.

appnp icon appnp

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

correctandsmooth icon correctandsmooth

[ICLR 2021] Combining Label Propagation and Simple Models Out-performs Graph Neural Networks (https://arxiv.org/abs/2010.13993)

deformable-detr icon deformable-detr

Deformable DETR: Deformable Transformers for End-to-End Object Detection.

detr icon detr

End-to-End Object Detection with Transformers

dgi icon dgi

Deep Graph Infomax (https://arxiv.org/abs/1809.10341)

eightpuzzle icon eightpuzzle

Solving Eight Puzzle Problems by Four Classic Search Algorithms (DFS, BFS, UCS, A*): A GUI Demo

gat icon gat

A PyTorch Implementation of Graph Attention Network (GAT, Petar V., ICLR 2018).

gcn icon gcn

A PyTorch Implementation of Graph Convolutional Network (GCN, T. Kipf, ICLR 2017)

gnn4nlp-papers icon gnn4nlp-papers

A list of recent papers about Graph Neural Network methods applied in NLP areas.

knowphish icon knowphish

[USENIX Security 2024] Official Repository of 'KnowPhish: Large Language Models Meet Multimodal Knowledge Graphs for Enhancing Reference-Based Phishing Detection'

m3s_pytorch icon m3s_pytorch

Pytorch implementation of "Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labeled Nodes"

nusthesis icon nusthesis

A LaTeX template for thesis of the National University of Singapore (NUS)

ocontact icon ocontact

O Contact: A Simple Material-style Android Contacts Manager. (Android Development Project 2018)

ocr icon ocr

A File Scanning and Converting Program Based on Optical Character Recognition (OCR)

phishpedia icon phishpedia

Official Implementation of "Phishpedia: A Hybrid Deep Learning Based Approach to Visually Identify Phishing Webpages" USENIX'21

pytorch-gan icon pytorch-gan

PyTorch implementations of Generative Adversarial Networks.

schedule icon schedule

Schedule for learning on graphs seminar

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