GitHub

MLPvibSpec is a suite of Python tools to train a multi-layer perceptron model to simulate dipole moments and polarizability tensors from an AIMD trajectory.

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).
IEEE

Accurate and Efficient Proximity Effect Correction for Electron Beam Lithography Based on Multilayer Perceptron Neural Network

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 ...