A CNN-LSTM model recovers the symbolic Hamiltonian from an image of its vector field on the plane, with 85 to 88 percent accuracy on a closed vocabulary of polynomial and trigonometric Hamiltonians.
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SymFlux: deep symbolic regression of Hamiltonian vector fields
A CNN-LSTM model recovers the symbolic Hamiltonian from an image of its vector field on the plane, with 85 to 88 percent accuracy on a closed vocabulary of polynomial and trigonometric Hamiltonians.