scBiG for representation learning of single-cell gene expression data based on bipartite graph embedding

[KDD'2023] "AdaGCL: Adaptive Graph Contrastive Learning for Recommendation"

[PAKDD 2021] Graph InfoClust: Leveraging cluster-level node information for unsupervised graph representation learning

Deep Graph Infomax (https://arxiv.org/abs/1809.10341)

Deep probabilistic analysis of single-cell and spatial omics data

scAce: an adaptive embedding and clustering method for scRNA-seq data

[WWW'22] Official PyTorch implementation for "Improving Graph Collaborative Filtering with Neighborhood-enriched Contrastive Learning".

PyTorch implementation of the InfoNCE loss for self-supervised learning.

The PyTorch implementation of LightGCN

[ICLR'2023] "LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation"

Submanifold sparse convolutional networks

李宏毅2021/2022/2023春季机器学习课程课件及作业

PyTorch implementation of "CiaoSR: Continuous Implicit Attention-in-Attention Network for Arbitrary-Scale Image Super-Resolution (CVPR2023)"

Torch code for our CVPR 2018 paper "Residual Dense Network for Image Super-Resolution" (Spotlight)

Learning Continuous Image Representation with Local Implicit Image Function, in CVPR 2021 (Oral)

Code for our paper "Multi-scale Guided Attention for Medical Image Segmentation"

Official code of "Deep Variational Network Toward Blind Image Restoration".

Python package for denoise and imputation of spatial transcriptomics using deep learning.

Cell clustering for spatial transcriptomics data with graph neural network

Comprehensive mapping of tissue cell architecture via integrated single cell and spatial transcriptomics (cell2location model)

A Fully Bayesian Inference of Tumor Microenvironment composition and gene expression

SpaGCN: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network

Official repo for paper Graph Neural Networks for Multimodal Single-Cell Data Integration

Probabilistic Alignment of Spatial Transcriptomics Experiments