The authors show that stochastic reconfiguration is L2 gradient descent on the unit sphere, and they derive projected inverse iteration, a shifted inverse iteration method for neural-network wavefunctions, with faster convergence on spin models.
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Functional Neural Wavefunction Optimization
The authors show that stochastic reconfiguration is L2 gradient descent on the unit sphere, and they derive projected inverse iteration, a shifted inverse iteration method for neural-network wavefunctions, with faster convergence on spin models.