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Found 2 papers, 2 papers with code
Sparse and Structured Hopfield Networks
Modern Hopfield networks have enjoyed recent interest due to their connection to attention in transformers.
Symplectic Momentum Neural Networks -- Using Discrete Variational Mechanics as a prior in Deep Learning
The combination of such formulation leads SyMos to be constrained towards preserving important geometric structures such as momentum and a symplectic form and learn from limited data.
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