利用散射变换的量子能量回归
Quantum Energy Regression using Scattering Transforms
摘要：
我们提出了一种新的方法来回归的量子力学能量的基础上的散射变换的中间电子密度表示。散射变换是一种用级联多尺度小波变换计算的深度卷积网络。它具有合适的量子能量回归的不变性和稳定性。这种新的框架消除了基于库仑矩阵的能量回归的基本限制，数值实验给出了平面分子的最新精度。
英文摘要：
We present a novel approach to the regression of quantum mechanical energies based on a scattering transform of an intermediate electron density representation. A scattering transform is a deep convolution network computed with a cascade of multiscale wavelet transforms. It possesses appropriate invariant and stability properties for quantum energy regression. This new framework removes fundamental limitations of Coulomb matrix based energy regressions, and numerical experiments give state-of-the-art accuracy over planar molecules.
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