y-yujie Goto Github PK

age

Source code and dataset for KDD 2020 paper "Adaptive Graph Encoder for Attributed Graph Embedding"

alacd-v1

lncRNA-drug

bigan-lncrna-disease-associations-prediction

bionev

Graph Embedding Evaluation / Code and Datasets for "Graph Embedding on Biomedical Networks: Methods, Applications, and Evaluations" (Bioinformatics 2020)

daestb

DAESTB: Inferring associations of small molecule-miRNA via a scalable tree boosting model based on deep autoencoder

deeplda

lncRNA-drug resistance

deepmne

DeepMNE: Deep Multi-Network Embedding for lncRNA-Disease Association Prediction

dgnnmda

dhcn

Codes for AAAI'21 paper 'Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation'

ekrrsmma

encflda

flaskproject

基于Flask框架构建的Web系统

gatcl2cd

Predicting CircRNA-Disease associations via feature convolution learning with heterogeneous graph attention network

gatecda

This code and data were provided for the paper "Predicting CircRNA-Drug Sensitivity Associations via Graph Attention Auto-Encoder"

gcn

Implementation of Graph Convolutional Networks in TensorFlow

gcnii

PyTorch implementation of "Simple and Deep Graph Convolutional Networks"

gde

SIGIR 2022 Paper: Less is More: Reweighting Important Spectral Graph Features for Recommendation

grpamda

a novel deep learning method to stydy miRNA-disease associations

gsmv

Learning global dependencies and multi-semantics within heterogeneous graph for predicting disease-related lncRNAs

hbrwrlda

HBRWRLDA: Predicting Potential LncRNA–Disease Associations Based on Hypergraph Bi-Random Walk with Restart

hgcl

[WSDM'2023] "Heterogeneous Graph Contrastive Learning for Recommendation"

hgclmda

hgnnlda

HGNNLDA: Predicting lncRNA-drug sensitivity associations via a dual channel hypergraph neural network

hrgcnlda

A computational model used to predict potential associations between lncRNAs and diseases

hygnn-drug-drug-interaction-prediction-via-hypergraph-neural-network

ipcarf_zr1

Using a combination of incremental principal component analysis (IPCA) and random forest (RF) algorithms and by integrating multiple similarity matrices, we propose a new algorithm (IPCARF) based on integrated machine learning technology for predicting lncRNA-disease associations.

l2-gcn

[CVPR 2020] L2-GCN: Layer-Wise and Learned Efficient Training of Graph Convolutional Networks

layer_refined

A Pytorch Recommendation Framework with Implicit Feedback.

learning-area

MDN 学习区示例中文版

learning-area-1

Github repo for the MDN Learning Area.