MLP Tutorial

Table of Contents

A. Machine Learning Models

• 1. Feedforward Neural Network Models
• 2. Gaussian Process Regression Models

B. Molecular Representations

• 3. Behler-Parrinello Symmetry Functions
• 4. A PyTorch implementation of Deep Potential-Smooth Edition (DeepPot-SE)

C. Machine Learning Potentials

• 5. Behler-Parrinello Fitting Neural Network with Machine Learning Potential (BP-FNN MLP) Models for the Claisen Rearrangement
• 6. Lesson 6: DeepPot-Smooth Edition Fitting Neural Network with Machine Learning Potentials (DeepPot-SE-FNN MLP)
• 7. Lesson 7: Behler-Parrinello Gaussian Process Regression (BP-GPR) for Machine Learning Potentials