Training Neural Network Potentials: Bayesian and Simulation-based Approaches

Training Neural Network Potentials: Bayesian and Simulation-based Approaches

Valence Labs via YouTube Direct link

- Force Matching

3 of 14

3 of 14

- Force Matching

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Training Neural Network Potentials: Bayesian and Simulation-based Approaches

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  1. 1 - Intro and Overview
  2. 2 - Outline: Training Neural Network Potentials
  3. 3 - Force Matching
  4. 4 - Relative Entropy Minimization
  5. 5 - Prior Potential: Delta Learning for GNN Potentials
  6. 6 - CG Water Model
  7. 7 - CG Alanine Dipeptide
  8. 8 - Bottom-Up/Top-Down Training
  9. 9 - Diferentiable Trajectory Reweighing DiffTRe
  10. 10 - Coarse-Grained Model of Water
  11. 11 - The Need for Uncertainty Quantification
  12. 12 - Lennard Jones Toy Example: Posterior Modes
  13. 13 - Summary and Outlook
  14. 14 - Q+A

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