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: Artificial neural networks (NNs) have become the de facto standard in machine learning. They allow learning highly nonlinear transformations in a plethora of applications. However, NNs ...