Assistant professor @Fudan AI3 Institute
Repositories
ShawXh/qip_cvpr24
ShawXh/node2ket
code and data for ICLR 2024 paper ''Node2ket: Efficient High-Dimensional Network Embedding in Quantum Hilbert Space''
ShawXh/ShawXh
ShawXh/BTWalk
Implementation of TKDE20 paper ''BTWalk: Branching Tree Random Walk for Multi-order Structured Network Embedding''
ShawXh/RNCE
The implementation for TKDE22 paper ''Learning Regularized Noise Contrastive Estimation for Robust Network Embedding''
ShawXh/gensim
Topic Modelling for Humans
ShawXh/DeepWalk-dgl
ShawXh/alp-baselines
Baselines for anchor link prediction (including MNA, PALE, IONE, FINAL, FRUI-P, CROSSMNA, REGAL)
ShawXh/awesome-ml4co
Awesome machine learning for combinatorial optimization papers.
ShawXh/Evaluate-Embedding
Python API to evaluate performance of network embedding on node classification with LIBLINEAR, following DeepWalk and LINE
ShawXh/POMO
codes for paper "POMO: Policy Optimization with Multiple Optima for Reinforcement Learning"
ShawXh/minimal
Minimal is a Jekyll theme for GitHub Pages
ShawXh/TSP_Transformer
Code for TSP Transformer
ShawXh/dgl
Python package built to ease deep learning on graph, on top of existing DL frameworks.
ShawXh/graphlet_extract
Extract graphlet features with pure python
ShawXh/MakeCodeGreatAgain
Coding in every naive day
ShawXh/DHNE
the Implementation of "Structural Deep Embedding for Hyper-Networks"
ShawXh/deepwalk-c
DeepWalk implementation in C++
ShawXh/verse
Reference implementation of the paper VERSE: Versatile Graph Embeddings from Similarity Measures
ShawXh/netgan
Implementation of the paper "NetGAN: Generating Graphs via Random Walks".
ShawXh/graph-generation
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models
ShawXh/jekyll-pithy
a jekyll theme
ShawXh/graph_nets
Build Graph Nets in Tensorflow
ShawXh/pyecharts
🎨 Python Echarts Plotting Library
ShawXh/netalignSP
ShawXh/netalign
Supporting codes for the manuscript: Message Passing Algorithms for Sparse Network Alignment. This package contains datasets and programs to solve network alignment problems written in the Matlab language.
ShawXh/crmp
Predicting Anchor Links between Heterogeneous Social Networks
ShawXh/FINAL-network-alignment-KDD16
ShawXh/IONE
Source Code and data for IJCAI 2016 paper "Aligning Users Across Social Networks Using Network Embedding"