NSLab-CUK / S-CGIBLinks
Subgraph-conditioned Graph Information Bottleneck (S-CGIB) is a novel architecture for pre-training Graph Neural Networks in molecular property prediction and developed by NS Lab, CUK based on pure PyTorch backend.
☆13Updated 3 months ago
Alternatives and similar repositories for S-CGIB
Users that are interested in S-CGIB are comparing it to the libraries listed below
Sorting:
- Official implementation of NeurIPS'21 paper"Motif-based Graph Self-Supervised Learning for Molecular Property Prediction"☆126Updated 2 years ago
- Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph Generation☆34Updated 2 years ago
- [ICLR 2023] "Mole-BERT: Rethinking Pre-training Graph Neural Networks for Molecules"☆126Updated 2 years ago
- The official codes and implementations of HimGNN model in paper:"HimGNN:a novel hierarchical molecular representations learning framewor…☆21Updated 2 years ago
- Official code implementation of PremuNet model.☆16Updated 4 months ago
- codes for KPGT (Knowledge-guided Pre-training of Graph Transformer)☆116Updated last year
- Implementation for the paper MoCL: Contrastive Learning on Molecular Graph with multi-level Domain Knowledge☆41Updated 2 years ago
- [NeurIPS 2023] "Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules"☆39Updated last year
- Learning to Group Auxiliary Datasets for Molecule, NeurIPS2023☆19Updated last year
- [NeurIPS 2024] Implementation of "Enhancing Graph Transformers with Hierarchical Distance Structural Encoding"☆16Updated 5 months ago
- The implementation of the paper "Multi-Modal Representation Learning for Molecular Property Prediction: Sequence, Graph, Geometry".☆47Updated 10 months ago
- Official implementation of paper: MolAE: Auto-Encoder Based Molecular Representation Learning With 3D Cloze Test Objective (icml 2024)☆12Updated last year
- Implementation of Fragment-based Pretraining and Finetuning on Molecular Graphs (NeurIPS 2023)☆21Updated last year
- Official implementation for the paper "Learning Substructure Invariance for Out-of-Distribution Molecular Representations" (NeurIPS 2022)…☆61Updated 2 years ago
- Pre-training Molecular Graph Representation with 3D Geometry, ICLR'22 (https://openreview.net/forum?id=xQUe1pOKPam)☆200Updated 3 years ago
- Official implementation for Learning Invariant Molecular Representation in Latent Discrete Space (NeurIPS 2023)☆21Updated 2 years ago
- A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining, ICML'23☆33Updated last year
- ☆14Updated 2 years ago
- The official implementation of NeurIPS2024 paper "SubgDiff: A Subgraph Diffusion Model to Improve Molecular Representation Learning."☆10Updated 5 months ago
- Code and Data for the paper: Graph Sampling-based Meta-Learning for Molecular Property Prediction [IJCAI2023]☆18Updated 2 years ago
- ☆28Updated last year
- ☆30Updated 4 years ago
- Codes for "Property-Aware Relation Networks for Few-shot Molecular Property Prediction (NeurIPS 2021)".☆50Updated 3 years ago
- The official source code for "Conditional Graph Information Bottleneck for Molecular Relational Learning".☆44Updated 2 years ago
- ☆21Updated 2 years ago
- Code for AAAI 2024 paper "PSC-CPI: Multi-Scale Protein Sequence-Structure Contrasting for Efficient and Generalizable Compound-Protein In…☆28Updated 8 months ago
- Triplet Graph Transformer☆47Updated last month
- Official implementation for AAAI 2022 paper: "GeomGCL: Geometric Graph Contrastive Learning for Molecular Property Prediction".☆22Updated 3 years ago
- [AAAI 2023] The implementation for the paper "Energy-Motivated Equivariant Pretraining for 3D Molecular Graphs"☆33Updated last year
- GeoSSL: Molecular Geometry Pretraining with SE(3)-Invariant Denoising Distance Matching, ICLR'23 (https://openreview.net/forum?id=CjTHVo1…☆47Updated 2 years ago