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Robust PDF Document Conversion Using Recurrent Neural Networks
In this paper, we present a novel approach to document structure recovery in PDF using recurrent neural networks to process the low-level PDF data representation directly, instead of relying on a visual re-interpretation of the rendered PDF page, as has been proposed in previous literature.
A step toward a reinforcement learning de novo genome assembler
Reinforcement learning has proven promising for solving complex activities without supervision - such games - and there is a pressing need to understand the limits of this approach to 'real' problems, such as the DFA problem.
Software tools for quantum control: Improving quantum computer performance through noise and error suppression
Manipulating quantum computing hardware in the presence of imperfect devices and control systems is a central challenge in realizing useful quantum computers.
Quantum Physics
