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Scaling down Deep Learning
Though deep learning models have taken on commercial and political relev...
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Lagrangian Neural Networks
Accurate models of the world are built upon notions of its underlying sy...
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Neural reparameterization improves structural optimization
Structural optimization is a popular method for designing objects such a...
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Hamiltonian Neural Networks
Even though neural networks enjoy widespread use, they still struggle to...
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Learning Finite State Representations of Recurrent Policy Networks
Recurrent neural networks (RNNs) are an effective representation of cont...
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Visualizing and Understanding Atari Agents
Deep reinforcement learning (deep RL) agents have achieved remarkable su...
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Learning the Enigma with Recurrent Neural Networks
Recurrent neural networks (RNNs) represent the state of the art in trans...
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Sam Greydanus
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