Pinned Repositories
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
CecilePereiraTotal's Repositories
CecilePereiraTotal/edbo
Experimental Design via Bayesian Optimization
CecilePereiraTotal/kGCN
A graph-based deep learning framework for life science
CecilePereiraTotal/fastbook
The fastai book, published as Jupyter Notebooks
CecilePereiraTotal/molgym
Reinforcement Learning for Molecular Design Guided by Quantum Mechanics
CecilePereiraTotal/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.
CecilePereiraTotal/deepchem-PUBLIC
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
CecilePereiraTotal/SMILES-X-PUBLIC
Autonomous characterization of molecular compounds from small datasets without descriptors
CecilePereiraTotal/ChemOS
CecilePereiraTotal/chemprop
Message Passing Neural Networks for Molecule Property Prediction
CecilePereiraTotal/NUS_AMDworkshop
Codes for the NUS_AMD_workshop
CecilePereiraTotal/active-learning
CecilePereiraTotal/ORGAN
Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models
CecilePereiraTotal/selfies
Robust representation of semantically constrained graphs, in particular for molecules in chemistry
CecilePereiraTotal/Fe_Si_Bayes_code
Fe_Si_Bayes_code
CecilePereiraTotal/ChemTS
Molecule Design using Monte Carlo Tree Search with Neural Rollout
CecilePereiraTotal/MCTS
Python Implementations of Monte Carlo Tree Search