6 citations · 9 across the 4 of their papers we have counts for
4 papers
Nuclear-physics-guided Gaussian Processes
Javier Rozalén Sarmiento, Hristijan Kochankovski, Arnau Rios +1
Gaussian Process Regression is a powerful nonparametric Bayesian method that provides both predictions and principled uncertainty estimates in closed form. The majority of past app…
Quantum Dynamics with Time-Dependent Neural Quantum States
Alejandro Romero-Ros, Javier Rozalén Sarmiento, Arnau Rios
We present proof-of-principle time-dependent neural quantum state (NQS) simulations to illustrate the ability of this approach to effectively capture key aspects of quantum dynamic…
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 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…