Junseok0207 / scGPCL
The official source code for "Deep single-cell RNA-seq data clustering with graph prototypical contrastive learning", accepted at Bioinformatics (Volume 39, June 2023) and 2023 ICML workshop on Computational Biology.
☆19Updated last year
Related projects ⓘ
Alternatives and complementary repositories for scGPCL
- The official source code for "Single-cell RNA-seq data imputation using Feature Propagation", accepted at 2023 ICML Workshop on Computati…☆11Updated last year
- The official source code for "S-Mixup: Structural Mixup for Graph Neural Networks", accepted at CIKM 2023 (Short Paper).☆18Updated last year
- The official source code for "Vision Language Model is NOT All You Need: Augmentation Strategies for Molecule Language Model".☆11Updated 3 months ago
- The official source code for "Relational Self-Supervised Learning on Graphs"☆23Updated 2 years ago
- The official source code for Task-Equivariant Graph Few-shot Learning (TEG) at KDD 2023.☆23Updated 11 months ago
- The official source code for "GraFN: Semi-Supervised Node Classification on Graph with Few Labels via Non-Parametric Distribution Assignm…☆24Updated 2 years ago
- Pytorch Implmentation of Meta Attack via Contrastive Surrogate Objective☆10Updated 6 months ago
- [ECCV 2024] Code for the paper "Mew: Multiplexed Immunofluorescence Image Analysis through an Efficient Multiplex Network"☆10Updated 3 months ago
- The official source code for Similarity Preserving Adversarial Graph Contrastive Learning (SP-AGCL) at KDD 2023.☆23Updated 10 months ago
- The official source code for "LTE4G: Long-Tail Experts for Graph Neural Networks" paper, accepted at CIKM 2022.☆38Updated 2 years ago
- The official source code for "Shift-Robust Molecular Relational Learning with Causal Substructure"☆20Updated last year
- ☆21Updated 3 years ago
- GraphCDR: A graph neural network method with contrastive learning for cancer drug response prediction☆25Updated 3 years ago
- The official source code for "Augmentation-Free Self-Supervised Learning on Graphs"☆76Updated 2 years ago
- ☆12Updated last year
- Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"☆74Updated 2 years ago
- Code & data for ICLR'23 Spotlight paper "Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency".☆29Updated last year
- Pytorch implementation of "Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labeled Nodes"☆18Updated 2 years ago
- ☆37Updated 3 years ago
- [PAKDD 2021] Graph InfoClust: Leveraging cluster-level node information for unsupervised graph representation learning☆33Updated 2 years ago
- ☆14Updated last year
- PyTorch Implementation for "Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning" (AAAI2023)☆21Updated last year
- The official source code for "Conditional Graph Information Bottleneck for Molecular Relational Learning".☆39Updated last year
- ☆27Updated 3 years ago
- The official source code for "Class Label-aware Graph Anomaly Detection", accepted at CIKM 2023.☆15Updated last year
- A heterogeneous graph automatic meta-path learning method for drug-target interaction prediction☆11Updated last year
- The offical source code for [2023 NeurIPS] " Density of States Prediction of Crystalline Materials via Prompt-guided Multi-Modal Transfor…☆19Updated last month
- Ratioanle-aware Graph Contrastive Learning codebase☆39Updated last year
- [ICLR 2023] "Graph Domain Adaptation via Theory-Grounded Spectral Regularization" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen☆21Updated last year
- The code of "Attribute and Structure preserving Graph Contrastive Learning" (AAAI 2023 oral)☆20Updated 5 months ago