3 citations · 3 across the 3 of their papers we have counts for
3 papers
physics.comp-ph2026
Introduction to the artificial neural network-based variational Monte Carlo method
William Freitas
The construction of trial wave functions based on neural networks combined with the variational Monte Carlo method is discussed. The mathematical formulation for representing quant…
physics.comp-ph2024
Neural network-based nodal structures optimization for interacting fermionic systems
William Freitas, B. Abreu, S. A. Vitiello
Simulating strongly correlated fermionic systems remains a fundamental challenge in quantum physics, largely due to the sign problem in quantum Monte Carlo (QMC) methods. We presen…
physics.atm-clus2023★ 3 cited
Synergy between deep neural networks and the variational Monte Carlo method for small clusters
William Freitas, S. A. Vitiello
We introduce a neural network-based approach for modeling wave functions that satisfy Bose-Einstein statistics. Applying this model to small clusters (with N ranging from…