23 citations · 43 across the 4 of their papers we have counts for
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cs.NE2019
Hamiltonian Neural Networks
Sam Greydanus, Misko Dzamba, Jason Yosinski
Even though neural networks enjoy widespread use, they still struggle to learn the basic laws of physics. How might we endow them with better inductive biases? In this paper, we dr…
cs.NE2017★ 23 cited
Learning the Enigma with Recurrent Neural Networks
Sam Greydanus
Recurrent neural networks (RNNs) represent the state of the art in translation, image captioning, and speech recognition. They are also capable of learning algorithmic tasks such a…