6 citations · 11 across the 2 of their papers we have counts for
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nucl-th2024★ 6 cited
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…
nucl-th2023★ 5 cited
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…
nucl-th2019
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…