daiki-ko / Metric_MHG-VAELinks
☆10Updated 5 years ago
Alternatives and similar repositories for Metric_MHG-VAE
Users that are interested in Metric_MHG-VAE are comparing it to the libraries listed below
Sorting:
- Message Passing Neural Networks for Molecule Property Prediction☆11Updated 5 years ago
- Data and analysis scripts for understanding molecular entropies, including conformer flexibility☆12Updated 4 years ago
- ☆11Updated 6 years ago
- Official code for the publication "HyFactor: Hydrogen-count labelled graph-based defactorization Autoencoder".☆18Updated 2 years ago
- Source codes for 'A baseline for reliable molecular prediction models via Bayesian learning'☆29Updated 5 years ago
- ☆13Updated 6 years ago
- Bias-controlled 3D generative framework for structure-based ligand design☆17Updated 3 years ago
- Shows some of the ways molecule generation and optimization can go wrong☆17Updated 2 years ago
- A generative model for molecular generation via multi-step chemical reactions☆14Updated last year
- ☆16Updated last year
- Matrix factorization and deep learning for molecular property prediction☆13Updated 6 years ago
- ☆20Updated last year
- AutoCorrelation of Pharmacophore Features☆15Updated 2 years ago
- Tools and routines to calculate distances between synthesis routes and to cluster them.☆27Updated 7 months ago
- Implementation of "Chemical Design with GPU-based Ising Machine"☆13Updated 2 years ago
- ☆31Updated 7 years ago
- ☆12Updated 5 months ago
- A concise and easy-to-customize reimplementation of "ChemProp" (Yang et al, 2019) in PyTorch Geometric.☆23Updated 3 years ago
- Tree-Invent: A novel molecular generative model constrained with topological tree☆12Updated 2 years ago
- Supporting code for the paper «Leveraging molecular structure and bioactivity with chemical language models for drug design»☆11Updated 3 years ago
- SE(3)-equivariant point cloud networks for virtual screening☆24Updated 2 years ago
- ☆17Updated 4 years ago
- Force field-inspired molecular representation learning model☆21Updated 2 years ago
- EdgeSHAPer: Bond-Centric Shapley Value-Based Explanation Method for Graph Neural Networks☆27Updated 3 months ago
- Official Implementation of Expressivity and Generalization: Fragment-Biases for Molecular GNNs☆19Updated last year
- Comparing graph representations for molecular features prediction☆24Updated 2 years ago
- Bayesian Active Learning for Optimization and Uncertainty Quantification with Applications to Protein Docking☆13Updated 4 years ago
- Modeling Tanimoto distributions for RDKit☆18Updated 5 years ago
- coming soon☆28Updated 2 years ago
- Supporting models and data to doi 10.1021/acs.jcim.1c01163☆15Updated 3 years ago