YuanchenBei / Awesome-Deep-Graph-Learning-for-Drug-Discovery
A curated list of papers on deep graph learning for drug discovery (DGL4DD).
☆13Updated last year
Alternatives and similar repositories for Awesome-Deep-Graph-Learning-for-Drug-Discovery:
Users that are interested in Awesome-Deep-Graph-Learning-for-Drug-Discovery are comparing it to the libraries listed below
- Code for AAAI24 paper Text-Guided Molecule Generation with Diffusion Language Model☆18Updated 8 months ago
- The code for "Graph Diffusion Transformer for Multi-Conditional Molecular Generation"☆61Updated 2 months ago
- [ICLR 2023] "Mole-BERT: Rethinking Pre-training Graph Neural Networks for Molecules"☆117Updated last year
- The implementation of the paper "Multi-Modal Representation Learning for Molecular Property Prediction: Sequence, Graph, Geometry".☆41Updated 4 months ago
- [ICLR 2024] MARCEL: Machine Learning over Molecular Conformer Ensembles☆42Updated last year
- Multi-modal Molecule Structure-text Model for Text-based Editing and Retrieval, Nat Mach Intell 2023 (https://www.nature.com/articles/s42…☆224Updated 3 months ago
- Learning to Group Auxiliary Datasets for Molecule, NeurIPS2023☆19Updated last year
- Source code of "Improving Equivariant Graph Neural Networks on Large Geometric Graphs via Virtual Nodes Learning"☆24Updated 4 months ago
- ☆30Updated 9 months ago
- codes for KPGT (Knowledge-guided Pre-training of Graph Transformer)☆106Updated 7 months ago
- ☆28Updated last year
- Implementation of Fragment-based Pretraining and Finetuning on Molecular Graphs (NeurIPS 2023)☆19Updated 10 months ago
- Geom3D: Geometric Modeling on 3D Structures, NeurIPS 2023☆118Updated 10 months ago
- Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph Generation☆33Updated last year
- NeurIPS24: Aligning Target-Aware Molecule Diffusion Models with Exact Energy Optimization☆30Updated 3 weeks ago
- ICML2024: Equivariant Graph Neural Operator for Modeling 3D Dynamics☆56Updated last year
- Official implementation for AAAI 2022 paper: "GeomGCL: Geometric Graph Contrastive Learning for Molecular Property Prediction".☆22Updated 2 years ago
- Working collection of papers, repos and models of transformer based language models trained or tuned for the Chemical domain, from natura…☆59Updated last year
- [NeurIPS 2024] Implementation of "Enhancing Graph Transformers with Hierarchical Distance Structural Encoding"☆14Updated 5 months ago
- Code for AAAI 2024 paper "PSC-CPI: Multi-Scale Protein Sequence-Structure Contrasting for Efficient and Generalizable Compound-Protein In…☆26Updated 2 months ago
- ☆24Updated 2 years ago
- List of Geometric GNNs for 3D atomic systems☆105Updated last year
- The official implementation of dual-view molecule pre-training.☆41Updated 3 years ago
- ☆121Updated last month
- The official codes and implementations of HimGNN model in paper:"HimGNN:a novel hierarchical molecular representations learning framewor…☆17Updated last year
- CrysMMNet: Multimodal Representation for Crystal Property Prediction (UAI-2023)☆16Updated 9 months ago
- Making self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.☆166Updated last year
- MolDiff: Addressing the Atom-Bond Inconsistency Problem in 3D Molecule Diffusion Generation☆50Updated 9 months ago
- [NeurIPS 2023] "Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules"☆36Updated last year
- Implementation for NeurIPS 2023 paper "Equivariant Flow Matching with Hybrid Probability Transport for 3D Molecule Generation"☆33Updated 10 months ago