Showing 2026Show all
2 papers · 1 filter
physics.comp-ph2026
A Boson-informed neural network for Ground States of Many-Body Schrödinger equations
Zhizhong Kong, Jerry Zhijian Yang, Cheng Yuan +1
We propose a symmetry-preserving Boson-informed neural network (BINN) for the variational Monte Carlo computation of interacting-boson ground states in continuous space. The framew…
cs.LG2026
Multi-stage neural operator learning with application for convolutions
Zhiping Mao, Zhenye Wen, Yong Zhang +1
Convolution integrals widely exist in applications, and to enable fast and accurate computations, this paper introduces two general multi-stage neural operator learning frameworks.…