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We develop a framework for combining differentiable programming languages with neural networks.
Catastrophic interference in connectionist networks: The sequential learning problem
McCloskey, Michael and Cohen, Neal J · 1989
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Connectionist models of recognition memory: constraints imposed by learning and forgetting functions
Ratcliff, Roger · 1990
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Thrun, Sebastian · 1994
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Catastrophic forgetting, rehearsal and pseudorehearsal
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Is learning the n-th thing any easier than learning the first?
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The task rehearsal method of life-long learning: Overcoming impoverished data
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The German Traffic Sign Recognition Benchmark: A multi-class classification competition
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Learning task grouping and overlap in multi-task learning
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Ruvolo, Paul and Eaton, Eric · 2013
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Gaunt, Alexander L., Brockschmidt, Marc, Singh, Rishabh, Kushman, Nate, Kohli, Pushmeet, Taylor, Jonathan, and Tarlow, Daniel · 2016
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Hybrid computing using a neural network with dynamic external memory
Graves, Alex, Wayne, Greg, Reynolds, Malcolm, Harley, Tim, Danihelka, Ivo, Grabska-Barwińska, Agnieszka, Colmenarejo, Sergio Gómez, Grefenstette, Edward, Ramalho, Tiago, Agapiou, John, et al · 2016
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Kaiser, Łukasz and Sutskever, Ilya · 2016
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Neelakantan, Arvind, Le, Quoc V., and Sutskever, Ilya · 2016
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Extensions and limitations of the neural GPU
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