reinforcement learning

Symmetry-Aware Actor-Critic for 3D Molecular Design

We propose an actor-critic architecture for 3D molecular design that exploits the symmetries of the design process using spherical harmonics.

Reinforcement Learning for Molecular Design Guided by Quantum Mechanics

We present a reinforcement learning formulation that enables molecular design directly in Cartesian coordinates.

Factored Contextual Policy Search with Bayesian Optimization

We factor contexts for contextual policy search into environment and target components, such that experience can be directly generalized over target contexts.