63 citations · 77 across the 4 of their papers we have counts for
4 papers
Second-order optimisation strategies for neural network quantum states
M. Drissi, J. W. T. Keeble, J. Rozalén Sarmiento +1
The Variational Monte Carlo method has recently seen important advances through the use of neural network quantum states. While more and more sophisticated ansätze have been design…
Machine learning one-dimensional spinless trapped fermionic systems with neural-network quantum states
J. W. T. Keeble, M. Drissi, A. Rojo-Francàs +2
We compute the ground-state properties of fully polarized, trapped, one-dimensional fermionic systems interacting through a gaussian potential. We use an antisymmetric artificial n…
Machine learning the deuteron: new architectures and uncertainty quantification
J Rozalén Sarmiento, J W T Keeble, A Rios
We solve the ground state of the deuteron using a variational neural network ansatz for the wave function in momentum space. This ansatz provides a flexible representation of both…
Machine learning the deuteron
J. W. T. Keeble, A. Rios
We use machine learning techniques to solve the nuclear two-body bound state problem, the deuteron. We use a minimal one-layer, feed-forward neural network to represent the deutero…