Deep Action Sequence Learning for Causal Shape Transformation

17 May 2016Kin Gwn LoreDaniel StoeckleinMichael DaviesBaskar GanapathysubramanianSoumik Sarkar

Deep learning became the method of choice in recent year for solving a wide variety of predictive analytics tasks. For sequence prediction, recurrent neural networks (RNN) are often the go-to architecture for exploiting sequential information where the output is dependent on previous computation... (read more)

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