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MLP Tutorial
MLP Tutorial
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
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