GFlowNets for AI-driven scientific discovery
Moksh Jain, Tristan Deleu, Jason Hartford, Chenghao Liu, Álex Hernández-García, Yoshua Bengio
Abstract
GFlowNets provide a general probabilistic framework for accelerating the computational phase of the scientific discovery process, which is crucial for tackling pressing challenges posed by global pandemics and the climate crisis.
Topics & Concepts
Computer scienceMachine learningData scienceScientific discoveryArtificial intelligenceLeverage (statistics)Pipeline (software)Context (archaeology)Probabilistic logicUncertainty quantificationBig dataData miningPaleontologyBiologyProgramming languagePsychologyCognitive scienceMachine Learning in Materials ScienceComputational Drug Discovery MethodsMachine Learning and Data Classification