liugangcode / Data-Centric-TransferLinks
[NeurIPS'23] Source code of "Data-Centric Learning from Unlabeled Graphs with Diffusion Model": A data-centric transfer learning framework with diffusion model on graphs.
☆22Updated 8 months ago
Alternatives and similar repositories for Data-Centric-Transfer
Users that are interested in Data-Centric-Transfer are comparing it to the libraries listed below
Sorting:
- [KDD'22] Source codes of "Graph Rationalization with Environment-based Augmentations"☆47Updated 10 months ago
- [NeurIPS 2023] "Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules"☆40Updated last year
- Ratioanle-aware Graph Contrastive Learning codebase☆44Updated 2 years ago
- The code for GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning☆66Updated last year
- [ICLR 2024] VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs☆103Updated last year
- The official source code for "Conditional Graph Information Bottleneck for Molecular Relational Learning".☆44Updated 2 years ago
- Official implementation for the paper "Learning Substructure Invariance for Out-of-Distribution Molecular Representations" (NeurIPS 2022)…☆62Updated 2 years ago
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆45Updated 2 years ago
- Source code for From Stars to Subgraphs (ICLR 2022)☆72Updated last year
- [ICLR 2023] Learnable Randomness Injection (LRI) for interpretable Geometric Deep Learning.☆24Updated 2 years ago
- Official implementation of NeurIPS'21 paper"Motif-based Graph Self-Supervised Learning for Molecular Property Prediction"☆127Updated 2 years ago
- Implementation of Self-supervised Graph-level Representation Learning with Local and Global Structure (ICML 2021).☆80Updated 4 years ago
- Official implementation for Learning Invariant Molecular Representation in Latent Discrete Space (NeurIPS 2023)☆23Updated 2 years ago
- Unified Graph Transformer (UGT) is a novel Graph Transformer model specialised in preserving both local and global graph structures and d…☆28Updated 6 months ago
- Official Implementation of "D4Explainer: In-Distribution GNN Explanations via Discrete Denoising Diffusion"☆24Updated 2 years ago
- ☆16Updated 2 years ago
- Implementation of ICML'24 Paper "Less is More: on the Over-Globalizing Problem in Graph Transformers"☆46Updated last year
- [NeurIPS'23] Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling. Haotao Wang, Ziyu Jiang, Yuning Y…☆57Updated 2 years ago
- Towards Multi-Grained Explainability for Graph Neural Networks (NeurIPS 2021) + Pytorch Implementation of GNN attribution methods☆69Updated 11 months ago
- [ICML 2022] Local Augmentation for Graph Neural Networks☆66Updated last week
- GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)☆34Updated last year
- Code and Data for the paper: Molecular Contrastive Learning with Chemical Element Knowledge Graph [AAAI 2022]☆91Updated 2 years ago
- [NeurIPS 2023] Does Invariant Graph Learning via Environment Augmentation Learn Invariance?☆22Updated last year
- [ICML 2024] Code for Pairwise Alignment Improves Graph Domain Adaptation (Pair-Align)☆14Updated last year
- Rex Ying's Ph.D. Thesis, Stanford University☆41Updated 3 years ago
- Code implementation for paper "Can Large Language Models Empower Molecular Property Prediction?"☆39Updated 2 years ago
- Edge-Augmented Graph Transformer☆80Updated last year
- CIKM 2021: Pooling Architecture Search for Graph Classification☆20Updated 3 years ago
- This is an official implementation for "GRIT: Graph Inductive Biases in Transformers without Message Passing".☆127Updated 5 months ago
- EDGE: Efficient and Degree-Guided Graph Generation via Discrete Diffusion Modeling☆67Updated 8 months ago