Pinned Repositories
2018-MLJ-Semi-supervised-feature-selection
Matlab code of the paper "Simple Strategies for Semi-Supervised Feature Selection" published in Machine Learning Journal
Active-GBSSL
This is a project of my paper related to active learning and graph based semi-supervised learning, which is published on ICME 2014. The project is written by matlab
adversarial_training_methods
Implementation of the methods proposed in **Adversarial Training Methods for Semi-Supervised Text Classification** on IMDB dataset (without pre-training)
AI00
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].
attention-transfer
Improving Convolutional Networks via Attention Transfer (ICLR 2017)
awesome-contrastive-self-supervised-learning
A comprehensive list of awesome contrastive self-supervised learning papers.
awesome-deep-gnn
Papers about developing deep Graph Neural Networks (GNNs)
awesome-graph-self-supervised-learning
Awesome Graph Self-Supervised Learning
awesome-knowledge-distillation
Awesome Knowledge Distillation
WangeJie's Repositories
WangeJie/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].
WangeJie/awesome-contrastive-self-supervised-learning
A comprehensive list of awesome contrastive self-supervised learning papers.
WangeJie/awesome-deep-gnn
Papers about developing deep Graph Neural Networks (GNNs)
WangeJie/awesome-graph-self-supervised-learning
Awesome Graph Self-Supervised Learning
WangeJie/awesome-network-embedding
A curated list of network embedding techniques.
WangeJie/awesome-self-supervised-gnn
Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).
WangeJie/awesome-self-supervised-learning
A curated list of awesome self-supervised methods
WangeJie/awesome-self-supervised-learning-for-graphs
A curated list for awesome self-supervised learning for graphs.
WangeJie/cs229t
Statistical Learning Theory (CS229T) Lecture Notes
WangeJie/deep-symmetry
WangeJie/deep_gcns
Tensorflow Repo for "DeepGCNs: Can GCNs Go as Deep as CNNs?" ICCV2019 Oral https://deepgcns.org
WangeJie/dgl
Python package built to ease deep learning on graph, on top of existing DL frameworks.
WangeJie/fastText
Library for fast text representation and classification.
WangeJie/gae
Implementation of Graph Auto-Encoders in TensorFlow
WangeJie/gae_in_pytorch
Graph Auto-Encoder in PyTorch
WangeJie/GATE
Graph Attention Auto-Encoders
WangeJie/gcn
Implementation of Graph Convolutional Networks in TensorFlow
WangeJie/google-research
Google AI Research
WangeJie/gravity_graph_autoencoders
Source code from the CIKM 2019 article "Gravity-Inspired Graph Autoencoders for Directed Link Prediction" by G. Salha, S. Limnios, R. Hennequin, V.A. Tran and M. Vazirgiannis
WangeJie/GSSNN
The implementation of our AAAI 2020 paper "GSSNN: Graph Smoothing Splines Neural Network".
WangeJie/icml18-jtnn
Junction Tree Variational Autoencoder for Molecular Graph Generation (ICML 2018)
WangeJie/k-gnn
Source code for our AAAI paper "Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks".
WangeJie/linear_graph_autoencoders
Source code from the NeurIPS 2019 workshop article "Keep It Simple: Graph Autoencoders Without Graph Convolutional Networks" (G. Salha, R. Hennequin, M. Vazirgiannis) + k-core framework implementation from IJCAI 2019 article "A Degeneracy Framework for Scalable Graph Autoencoders" (G. Salha, R. Hennequin, V.A. Tran, M. Vazirgiannis)
WangeJie/mvGAE
Drug Similarity Integration Through Attentive Multi-view Graph Auto-Encoders (IJCAI 2018)
WangeJie/NLP-progress
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
WangeJie/RWR-GAE
Code for the paper "RWR-GAE: Random Walk Regularized Graph Auto Encoder"
WangeJie/Schedule
Schedule for learning on graphs seminar
WangeJie/see
Code for the AAAI 2018 publication "SEE: Towards Semi-Supervised End-to-End Scene Text Recognition"
WangeJie/solo-learn
solo-learn: a library of self-supervised methods for visual representation learning powered by Pytorch Lightning
WangeJie/wDAE_GNN_FewShot
Generating Classification Weights with GNN Denoising Autoencoders for Few-Shot Learning