Jiaxing Xu (AngusMonroe)

AngusMonroe

Geek Repo

Company:Nanyang Technological University

Location:Singapore

Home Page:https://angusmonroe.cn

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Jiaxing Xu's repositories

knowledge-driven-dialogue-lic2019

2019 语言与智能技术竞赛-知识驱动对话 B榜第5名源码和模型

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Active-NER

Bayesian Deep Active Learning for Named entity recognition (NER)

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BLSTM-CRF-NER

BiLSTM+CNN+CRF NER, using pytorch

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Graph-Classification-Baseline

A framework of graph classification baselines which including TUDataset Loader, GNN models and visualization.

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CS224n

CS224n: Natural Language Processing with Deep Learning

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KarateGCN

A pytorch implement for GCN on Zachary’s karate club dataset.

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ContrastPool

[IEEE TMI 2024] Contrastive Graph Pooling for Explainable Classification of Brain Networks

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GraphPaperSurvey

A survey for graph related paper.

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UnionSNN

[AAAI 2024] Union Subgraph Neural Networks (UnionSNN)

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Structural-RNN

Structural RNN for trajectory prediction using PyTorch

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DidiBigData

BUAA Big Data and Cloud Computing 2019 teamwork

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GAT-pytorch

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

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GNN-Dialog-Agent

A multiturn seq2seq chatbot with GNN implemented by PyTorch.

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LeetCode

LeetCode Problems' Solutions

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MultiturnChatbot

A multiturn seq2seq chatbot implement by pytorch with Cornell Movie-Dialogs Corpus.

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benchmarking-gnns

Repository for benchmarking graph neural networks

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ChineseBQB

🇨🇳Chinese sticker pack,More joy / 表情包的博物馆, Github最有毒的仓库, **表情包大集合, 聚欢乐~

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CS224W

CS224W: Machine Learning with Graphs

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DataStructure

A simple tutorial of data structure based on Python 3

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Dialogflow-Chatbot

A chatbot using Dialogflow

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Graphlevel-SSL

Apply Graph Self-Supervised Learning methods to graph-level task(TUDataset, MolculeNet Datset)

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graphSAGE-pytorch

A PyTorch implementation of GraphSAGE. This package contains a PyTorch implementation of GraphSAGE.

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PassageShuffle

A tool that could shuffle sentences in a passage.

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Seq2seq-attention

Translation with a Seq2seq network and attention. The completely tutorial is in https://pytorch.org/tutorials/intermediate/seq2seq_translation_tutorial.html#

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