Whereas reinforcement learning has been applied with success to a range of robotic control problems in complex, uncertain environments, reliance on extensive data - typically sourced from simulation ...

Transfer learning speeds up model training by reusing pre-trained models for new tasks. It reduces data needs, enhancing performance and progress in new ML applications. Transfer learning is limited ...

Data sparseness is a major limiting factor for deep machine learning. In the natural sciences, data distributions are heterogeneous. For instance, in chemistry and early-phase drug discovery, compound ...