zaixizhang / MGSSLLinks
Official implementation of NeurIPS'21 paper"Motif-based Graph Self-Supervised Learning for Molecular Property Prediction"
☆122Updated last year
Alternatives and similar repositories for MGSSL
Users that are interested in MGSSL are comparing it to the libraries listed below
Sorting:
- Implementation for the paper MoCL: Contrastive Learning on Molecular Graph with multi-level Domain Knowledge☆41Updated last year
- Pre-training Molecular Graph Representation with 3D Geometry, ICLR'22 (https://openreview.net/forum?id=xQUe1pOKPam)☆193Updated 2 years ago
- codes for KPGT (Knowledge-guided Pre-training of Graph Transformer)☆114Updated 10 months ago
- [ICLR 2023] "Mole-BERT: Rethinking Pre-training Graph Neural Networks for Molecules"☆123Updated 2 years ago
- Codes for "Property-Aware Relation Networks for Few-shot Molecular Property Prediction (NeurIPS 2021)".☆49Updated 3 years ago
- Learning to Group Auxiliary Datasets for Molecule, NeurIPS2023☆19Updated last year
- Code and Data for the paper: Molecular Contrastive Learning with Chemical Element Knowledge Graph [AAAI 2022]☆91Updated last year
- Official implementation for the paper "Learning Substructure Invariance for Out-of-Distribution Molecular Representations" (NeurIPS 2022)…☆61Updated 2 years ago
- Multi-view Graph Contrastive Representation Learning for Drug-drug Interaction Prediction☆44Updated 3 years ago
- Official PyTorch implementation of "Molecular Representation Learning via Heterogeneous Motif Graph Neural Networks"☆37Updated 2 years ago
- MolRep: A Deep Representation Learning Library for Molecular Property Prediction☆129Updated 10 months ago
- Code of our IJCAI2021 paper: "Learning Attributed Graph Representation with Communicative Message Passing Transformer"☆40Updated 3 years ago
- [KDD'22] Source codes of "Graph Rationalization with Environment-based Augmentations"☆45Updated 4 months ago
- This is a Pytorch implementation of the paper: Self-Supervised Graph Transformer on Large-Scale Molecular Data☆356Updated last month
- [NeurIPS 2023] "Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules"☆37Updated last year
- Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph Generation☆33Updated 2 years ago
- Code and data for the Nature Machine Intelligence paper "Knowledge graph-enhanced molecular contrastive learning with functional prompt".☆127Updated last year
- ☆64Updated 4 years ago
- ☆169Updated 3 years ago
- Making self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.☆169Updated last year
- Implementation of MolCLR: "Molecular Contrastive Learning of Representations via Graph Neural Networks" in PyG.☆290Updated last year
- ☆28Updated 4 years ago
- Unified 2D and 3D Pre-Training of Molecular Representations☆30Updated 3 years ago
- MoFlow: an invertible flow model for generating molecular graphs☆140Updated 2 years ago
- ☆47Updated last year
- Implementation of Fragment-based Pretraining and Finetuning on Molecular Graphs (NeurIPS 2023)☆20Updated last year
- Multi-Objective Molecule Generation using Interpretable Substructures (ICML 2020)☆157Updated 2 years ago
- This repository contains a PyTorch implementation of the paper "Hierarchical Graph Representation Learning for the Prediction of Drug-Tar…☆12Updated 3 years ago
- This is the code of paper "De Novo Molecular Generation via Connection-aware Motif Mining". Zijie Geng, Shufang Xie, Yingce Xia, Lijun Wu…☆55Updated 6 months ago
- Subgraph-conditioned Graph Information Bottleneck (S-CGIB) is a novel architecture for pre-training Graph Neural Networks in molecular pr…☆13Updated 2 weeks ago