ML-dip.py takes as input cartesian coordinates (XYZ-traj1.xyz) and dipole moments (DIP-traj1.dat) from a trajectory, and outputs dipole moments corresponding to another trajectory (XYZ-traj2.xyz).

A Jupyter notebook for RNN model is also available. The used open dataset 'Household Power Consumption' available at https://archive.ics.uci.edu/ml/datasets ...

Abstract: Recently, Multilayer Perceptron (MLP) becomes the hotspot in the field of computer vision tasks. Without in-ductive bias, MLPs perform well on feature extraction and achieve amazing results.

Abstract: This paper proposes a proximity effect correction (PEC) method for electron beam lithography (EBL) using multilayer perceptron (MLP) neural network (NN). By leveraging the symmetric ...