A review of Bayesian Gaussian Process States for ab initio quantum chemistry, with new MNIST digit classification results reaching about 1.6% test error.
Backflow Correlations in the Hubbard Model: An Efficient Tool for the Study of the Metal-Insulator Transition and the Large-$U$ Limit
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Bayesian perspectives for quantum states and application to ab initio quantum chemistry
A review of Bayesian Gaussian Process States for ab initio quantum chemistry, with new MNIST digit classification results reaching about 1.6% test error.