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active-learning

chemos

chemprop

Message Passing Neural Networks for Molecule Property Prediction

chemts

Molecule Design using Monte Carlo Tree Search with Neural Rollout

deepchem-public

Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

edbo

Experimental Design via Bayesian Optimization

fastbook

The fastai book, published as Jupyter Notebooks

fe_si_bayes_code

Fe_Si_Bayes_code

kgcn

A graph-based deep learning framework for life science

mcts

Python Implementations of Monte Carlo Tree Search

molgym

Reinforcement Learning for Molecular Design Guided by Quantum Mechanics

next

NEXT is a machine learning system that runs in the cloud and makes it easy to develop, evaluate, and apply active learning in the real-world. Ask better questions. Get better results. Faster. Automated.

nus_amdworkshop

Codes for the NUS_AMD_workshop

organ

Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models

selfies

Robust representation of semantically constrained graphs, in particular for molecules in chemistry

smiles-x-public

Autonomous characterization of molecular compounds from small datasets without descriptors