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.
☆21Updated last month
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"☆45Updated 3 months ago
- The code for GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning☆62Updated last year
- Source code for From Stars to Subgraphs (ICLR 2022)☆70Updated last year
- [NeurIPS 2023] "Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules"☆37Updated last year
- Ratioanle-aware Graph Contrastive Learning codebase☆43Updated 2 years ago
- [ICML 2024] Code for Pairwise Alignment Improves Graph Domain Adaptation (Pair-Align)☆13Updated last year
- GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)☆31Updated last year
- Official implementation for the paper "Learning Substructure Invariance for Out-of-Distribution Molecular Representations" (NeurIPS 2022)…☆61Updated 2 years ago
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆45Updated last year
- [ICLR 2024] VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs☆100Updated last year
- Implementation of Self-supervised Graph-level Representation Learning with Local and Global Structure (ICML 2021).☆80Updated 4 years ago
- The official source code for "Conditional Graph Information Bottleneck for Molecular Relational Learning".☆42Updated 2 years ago
- Code implementation for paper "Can Large Language Models Empower Molecular Property Prediction?"☆38Updated 2 years ago
- [ICLR 2023] Learnable Randomness Injection (LRI) for interpretable Geometric Deep Learning.☆23Updated last year
- Implementation of ICML'24 Paper "Less is More: on the Over-Globalizing Problem in Graph Transformers"☆45Updated last year
- ☆16Updated last year
- Rex Ying's Ph.D. Thesis, Stanford University☆41Updated 3 years ago
- Official implementation of NeurIPS'21 paper"Motif-based Graph Self-Supervised Learning for Molecular Property Prediction"☆122Updated last year
- Unified Graph Transformer (UGT) is a novel Graph Transformer model specialised in preserving both local and global graph structures and d…☆27Updated 3 months ago
- Official Implementation of "D4Explainer: In-Distribution GNN Explanations via Discrete Denoising Diffusion"☆23Updated last year
- ☆53Updated 2 years ago
- [NeurIPS'23] Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling. Haotao Wang, Ziyu Jiang, Yuning Y…☆52Updated last year
- [NeurIPS 2024] Implementation of "Enhancing Graph Transformers with Hierarchical Distance Structural Encoding"☆15Updated last month
- This is the official code repository for "Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs", wh…☆88Updated last year
- NeurIPS'22 Spotlight paper "Hierarchical Graph Transformer with Adaptive Node Sampling"☆52Updated last year
- Edge-Augmented Graph Transformer☆77Updated last year
- [ICML 2022] Local Augmentation for Graph Neural Networks☆66Updated last year
- This is an official implementation for "GRIT: Graph Inductive Biases in Transformers without Message Passing".☆126Updated 7 months ago
- ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks(ICLR 2023)☆20Updated last year
- Code for Hi-GMAE: Hierarchical Graph Masked Autoencoders☆10Updated 5 months ago