susan1314's repositories
ARGA
This is a TensorFlow implementation of the Adversarially Regularized Graph Autoencoder(ARGA) model as described in our paper: Pan, S., Hu, R., Long, G., Jiang, J., Yao, L., & Zhang, C. (2018). Adversarially Regularized Graph Autoencoder for Graph Embedding, [https://www.ijcai.org/proceedings/2018/0362.pdf].
ClusterGCN
A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).
CS224W_Winter2021
CS224W Stanford Winter 2021 Homework solutions
CTR-GCN
[ICCV2021] Official code for "Channel-wise Topology Refinement Graph Convolution for Skeleton-Based Action Recognition"
Deep_GCN_Benchmarking
[Preprint] "Bag of Tricks for Training Deeper Graph Neural Networks A Comprehensive Benchmark Study" by Tianlong Chen*, Kaixiong Zhou*, Keyu Duan, Wenqing Zheng, Peihao Wang, Xia Hu, Zhangyang Wang
EvolveGCN
Code for EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
GeniePath-pytorch
This is a PyTorch implementation of the GeniePath model in <GeniePath: Graph Neural Networks with Adaptive Receptive Paths> (https://arxiv.org/abs/1802.00910)
Graph-Transformer
Universal Graph Transformer Self-Attention Networks (TheWebConf WWW 2022) (Pytorch and Tensorflow)
GraphGym
Platform for designing and evaluating Graph Neural Networks (GNN)
GraphWaveletNeuralNetwork
A PyTorch implementation of "Graph Wavelet Neural Network" (ICLR 2019)
imbalanced-learn
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
karateclub
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
ldgcnn
Linked Dynamic Graph CNN: Learning through Point Cloud by Linking Hierarchical Features
many-to-many-dijkstra
A predictive model developed to identify medium-voltage electrical distribution grid infrastructure using publicly available data sources.
OPF_SOC
Optimal power flow in power distribution grids using second order cone optimization
Power
Physics informed, deep-learning-based state estimation for distribution electrical grids. The study proposes using physical properties of the grid connectivity as a regularizer of a deep neural network training.
PyTorch-VAE
A Collection of Variational Autoencoders (VAE) in PyTorch.
qlstm
Example of a Quantum LSTM
RE-GCN
This is the official code release of the following paper: Zixuan Li, Xiaolong Jin, Wei Li, Saiping Guan, Jiafeng Guo, Huawei Shen, Yuanzhuo Wang and Xueqi Cheng. Temporal Knowledge Graph Reasoning Based on Evolutional Representation Learning
reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
RL-Adventure
Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL
RLstudy
study reinforcement learning
SciencePlots
Matplotlib styles for scientific plotting
SEAL-CI
A PyTorch implementation of "Semi-Supervised Graph Classification: A Hierarchical Graph Perspective" (WWW 2019)
siamese-triplet
Siamese and triplet networks with online pair/triplet mining in PyTorch
TDA-tutorial
A set of jupyter notebooks for the practice of TDA with the python Gudhi library together with popular machine learning and data sciences libraries.
UltraGCN
[CIKM'21] UltraGCN: Ultra Simplification of Graph Convolutional Networks for Recommendation
vgae_pytorch
This repository implements variational graph auto encoder by Thomas Kipf.