model

Neural quantum states

It’s recommended to use ResSum when one needs a deep NQS.

SingleDense(features, actfn, use_bias, ...)
RBM_Dense(features[, use_bias, dtype])	The restricted Boltzmann machine with one dense layer \(\psi(s) = \prod \cosh(W s + b)\).
SingleConv(channels, actfn[, use_bias, ...])	Network with one convolutional layer \(\psi(s) = \prod f(\mathrm{Conv}(s))\).
RBM_Conv(channels[, use_bias, dtype])	The restricted Boltzmann machine with one convolutional layer \(\psi(s) = \prod \cosh(\mathrm{Conv}(s))\).
ResProd(nblocks, channels, kernel_size, ...)	The convolutional residual network with a product in the end.
SchmittNet(depth, channels, kernel_size[, dtype])	CNN defined in PRL 125, 100503.
ResSum(nblocks, channels, kernel_size[, ...])	The convolutional residual network with a summation in the end.
Triangular_ResSum(nblocks, channels[, ...])	The ResSum equivalence for Triangular and TriangularB lattices.