SchNet

2000년 도입 · 논문 20편에서 사용

SchNet is an end-to-end deep neural network architecture based on continuous-filter convolutions. It follows the deep tensor neural network framework, i.e. atom-wise representations are constructed by starting from embedding vectors that characterize the atom type before introducing the configuration of the system by a series of interaction blocks.

출처: SchNet: A continuous-filter convolutional neural network for modeling quantum interactions

소개 논문: SchNet: A continuous-filter convolutional neural network for modeling quantum interactions