31 citations · 31 across the 3 of their papers we have counts for
3 papers
cond-mat.dis-nn2026
Gradient-estimator design overcomes trainability barriers in neural-network-based variational optimization
Yi-Ran Xue, Rui Wang, Baigeng Wang +1
Neural networks provide expressive representations for scientific computing. However, even sufficiently expressive networks can suffer training failure in weak-gradient regimes, li…
cond-mat.dis-nn2026
Low-variance estimators overcome the phase-gradient bottleneck in complex-valued neural quantum states
Yi-Ran Xue, Rui Wang, Baigeng Wang +1
Complex neural quantum states are difficult to optimize when their wavefunction phase carries gauge, chiral, fermionic, or topological structure. We show that the major failure mod…
quant-ph2021★ 31 cited
Neural network-based prediction of the secret-key rate of quantum key distribution
Min-Gang Zhou, Zhi-Ping Liu, Wen-Bo Liu +6
Numerical methods are widely used to calculate the secure key rate of many quantum key distribution protocols in practice, but they consume many computing resources and are too tim…