moleculediscovery / workshop2022Links
Machine learning for molecules workshop 2022
☆13Updated 2 years ago
Alternatives and similar repositories for workshop2022
Users that are interested in workshop2022 are comparing it to the libraries listed below
Sorting:
- Hierarchical template correction for chemical reactions☆18Updated last year
- Supporting models and data to doi 10.1021/acs.jcim.1c01163☆15Updated 3 years ago
- An experimental package for deep learning for molecular docking☆20Updated 5 years ago
- ☆23Updated 4 years ago
- Exploring protein-ligand binding affinity prediction with electron density-based geometric deep learning☆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
- https://arxiv.org/abs/2102.11439☆20Updated 4 years ago
- Library for training Gaussian Processes on Molecules☆36Updated 3 years ago
- A concise and easy-to-customize reimplementation of "ChemProp" (Yang et al, 2019) in PyTorch Geometric.☆23Updated 3 years ago
- Shows some of the ways molecule generation and optimization can go wrong☆17Updated 2 years ago
- ☆17Updated 2 years ago
- Graph Inference on MoLEcular Topology☆26Updated 2 years ago
- This is an updated version of the MolecularTransformer of Schwaller et. al.☆14Updated 3 years ago
- A high-quality hand-curated logD7.4 dataset of 1,130 compounds☆22Updated 8 years ago
- MolDesigner: Interactive Design of Efficacious Drugs with Deep Learning (NeurIPS 2020 Demo)☆16Updated 4 years ago
- ☆31Updated 3 years ago
- Synthetic coordinates for GNNs, as proposed in "Directional Message Passing on Molecular Graphs via Synthetic Coordinates" (NeurIPS 2021)☆31Updated 2 years ago
- Matrix factorization and deep learning for molecular property prediction☆13Updated 6 years ago
- Molecular Out-Of-Distribution☆39Updated 7 months ago
- Chemical representation learning paper in Digital Discovery☆63Updated last year
- Comparing graph representations for molecular features prediction☆24Updated 2 years ago
- IBM Molecule Generation Experience (MolGX) is a tool to accelerate an AI-driven design of new materials.☆15Updated 3 years ago
- RXN fork of OpenNMT-py - Open Source Neural Machine Translation in PyTorch☆26Updated last year
- VMD Audio/Text control with natural language☆19Updated 4 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
- Rapid experimentation and scaling of deep learning models on molecular and crystal graphs.☆75Updated 2 years ago
- Learning Neural Generative Dynamics for Molecular Conformation Generation (ICLR 2021)☆22Updated 4 years ago
- An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming (ICML'21)☆51Updated 4 years ago
- ☆31Updated 7 years ago