A Weak Convergence Viewpoint on Invertible Coarse-Graining

A Weak Convergence Viewpoint on Invertible Coarse-Graining

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Intro

1 of 12

1 of 12

Intro

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A Weak Convergence Viewpoint on Invertible Coarse-Graining

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  1. 1 Intro
  2. 2 The necessity of coarse-graining
  3. 3 Challenges in coarse-graining biomolecular systems
  4. 4 Why use machine learning in this setting?
  5. 5 Invertible, state-dependent coarse-graining
  6. 6 Flexible and useful embeddings
  7. 7 Thermodynamic consistency (Noid and Voth)
  8. 8 Weak thermodynamic consistency
  9. 9 Rigorously inverting the CG sampling
  10. 10 Necessary Sacrifices
  11. 11 Metastability in protein folding / misfolding
  12. 12 Large-and small-scale observables well-captured

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