151 citations · 151 across the 2 of their papers we have counts for
4 papers · 1 filter
DOCKSTRING: easy molecular docking yields better benchmarks for ligand design
Miguel García-Ortegón, Gregor N. C. Simm, Austin J. Tripp +3
The field of machine learning for drug discovery is witnessing an explosion of novel methods. These methods are often benchmarked on simple physicochemical properties such as solub…
Symmetry-Aware Actor-Critic for 3D Molecular Design
Gregor N. C. Simm, Robert Pinsler, Gábor Csányi +1
Automating molecular design using deep reinforcement learning (RL) has the potential to greatly accelerate the search for novel materials. Despite recent progress on leveraging gra…
Reinforcement Learning for Molecular Design Guided by Quantum Mechanics
Gregor N. C. Simm, Robert Pinsler, José Miguel Hernández-Lobato
Automating molecular design using deep reinforcement learning (RL) holds the promise of accelerating the discovery of new chemical compounds. Existing approaches work with molecula…
A Generative Model for Molecular Distance Geometry
Gregor N. C. Simm, José Miguel Hernández-Lobato
Great computational effort is invested in generating equilibrium states for molecular systems using, for example, Markov chain Monte Carlo. We present a probabilistic model that ge…