14 citations · 19 across the 4 of their papers we have counts for
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cs.LG2018★ 14 cited
Flow Shape Design for Microfluidic Devices Using Deep Reinforcement Learning
Xian Yeow Lee, Aditya Balu, Daniel Stoecklein +2
Microfluidic devices are utilized to control and direct flow behavior in a wide variety of applications, particularly in medical diagnostics. A particularly popular form of microfl…
cs.LG2016
Deep Action Sequence Learning for Causal Shape Transformation
Kin Gwn Lore, Daniel Stoecklein, Michael Davies +2
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 ofte…